U.S. patent number 10,042,564 [Application Number 14/707,999] was granted by the patent office on 2018-08-07 for accessing data while migrating storage of the data.
This patent grant is currently assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION. The grantee listed for this patent is CLEVERSAFE, INC.. Invention is credited to Andrew Baptist, Wesley Leggette, Manish Motwani.
United States Patent |
10,042,564 |
Motwani , et al. |
August 7, 2018 |
Accessing data while migrating storage of the data
Abstract
A method begins by a plurality of storage units of a dispersed
storage network (DSN) receiving updated properties of DSN memory.
The method continues with a first storage unit and a second storage
unit establishing a migration pairing and establishing a storage
migration mechanism for migrating storage of data between the first
and second storage units. While migrating the storage of data using
the storage migration mechanism, the method continues with the
first or the second storage unit receiving a data access request
regarding data effected by the migrating the storage of data,
determining status of the migrating storage of data, and
determining which of the first and second storage units is to
process the data access request based on the status to produce a
determined storage unit. The method continues with the determined
storage unit processing the data access request.
Inventors: |
Motwani; Manish (Chicago,
IL), Leggette; Wesley (Chicago, IL), Baptist; Andrew
(Mt. Pleasant, WI) |
Applicant: |
Name |
City |
State |
Country |
Type |
CLEVERSAFE, INC. |
Chicago |
IL |
US |
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Assignee: |
INTERNATIONAL BUSINESS MACHINES
CORPORATION (Armonk, NY)
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Family
ID: |
54930496 |
Appl.
No.: |
14/707,999 |
Filed: |
May 8, 2015 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20150378626 A1 |
Dec 31, 2015 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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62019126 |
Jun 30, 2014 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F
3/0685 (20130101); G06F 3/067 (20130101); G06F
3/0665 (20130101); G06F 3/0619 (20130101); G06F
3/0647 (20130101) |
Current International
Class: |
G06F
3/06 (20060101) |
References Cited
[Referenced By]
U.S. Patent Documents
Other References
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No. 11; Nov. 1979; pp. 612-613. cited by applicant .
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by applicant .
Chung; An Automatic Data Segmentation Method for 3D Measured Data
Points; National Taiwan University; pp. 1-8; 1998. cited by
applicant .
Plank, T1: Erasure Codes for Storage Applications; FAST2005, 4th
Usenix Conference on File Storage Technologies; Dec. 13-16, 2005;
pp. 1-74. cited by applicant .
Wildi; Java iSCSi Initiator; Master Thesis; Department of Computer
and Information Science, University of Konstanz; Feb. 2007; 60 pgs.
cited by applicant .
Legg; Lightweight Directory Access Protocol (LDAP): Syntaxes and
Matching Rules; IETF Network Working Group; RFC 4517; Jun. 2006;
pp. 1-50. cited by applicant .
Zeilenga; Lightweight Directory Access Protocol (LDAP):
Internationalized String Preparation; IETF Network Working Group;
RFC 4518; Jun. 2006; pp. 1-14. cited by applicant .
Smith; Lightweight Directory Access Protocol (LDAP): Uniform
Resource Locator; IETF Network Working Group; RFC 4516; Jun. 2006;
pp. 1-15. cited by applicant .
Smith; Lightweight Directory Access Protocol (LDAP): String
Representation of Search Filters; IETF Network Working Group; RFC
4515; Jun. 2006; pp. 1-12. cited by applicant .
Zeilenga; Lightweight Directory Access Protocol (LDAP): Directory
Information Models; IETF Network Working Group; RFC 4512; Jun.
2006; pp. 1-49. cited by applicant .
Sciberras; Lightweight Directory Access Protocol (LDAP): Schema for
User Applications; IETF Network Working Group; RFC 4519; Jun. 2006;
pp. 1-33. cited by applicant .
Harrison; Lightweight Directory Access Protocol (LDAP):
Authentication Methods and Security Mechanisms; IETF Network
Working Group; RFC 4513; Jun. 2006; pp. 1-32. cited by applicant
.
Zeilenga; Lightweight Directory Access Protocol (LDAP): Technical
Specification Road Map; IETF Network Working Group; RFC 4510; Jun.
2006; pp. 1-8. cited by applicant .
Zeilenga; Lightweight Directory Access Protocol (LDAP): String
Representation of Distinguished Names; IETF Network Working Group;
RFC 4514; Jun. 2006; pp. 1-15. cited by applicant .
Sermersheim; Lightweight Directory Access Protocol (LDAP): The
Protocol; IETF Network Working Group; RFC 4511; Jun. 2006; pp.
1-68. cited by applicant .
Satran, et al.; Internet Small Computer Systems Interface (iSCSI);
IETF Network Working Group; RFC 3720; Apr. 2004; pp. 1-257. cited
by applicant .
Xin, et al.; Evaluation of Distributed Recovery in Large-Scale
Storage Systems; 13th IEEE International Symposium on High
Performance Distributed Computing; Jun. 2004; pp. 172-181. cited by
applicant .
Kubiatowicz, et al.; OceanStore: An Architecture for Global-Scale
Persistent Storage; Proceedings of the Ninth International
Conference on Architectural Support for Programming Languages and
Operating Systems (ASPLOS 2000); Nov. 2000; pp. 1-12. cited by
applicant.
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Primary Examiner: Chan; Tracy
Attorney, Agent or Firm: Garlick & Markison Markison;
Timothy W. Tyson, Jr.; Harry S.
Parent Case Text
CROSS REFERENCE TO RELATED PATENTS
The present U.S. Utility patent application claims priority
pursuant to 35 U.S.C. .sctn. 119(e) to U.S. Provisional Application
No. 62/019,126, entitled "SELECTING STORAGE RESOURCES OF A
DISPERSED STORAGE NETWORK", filed Jun. 30, 2014, which is hereby
incorporated herein by reference in its entirety and made part of
the present U.S. Utility patent application for all purposes.
Claims
What is claimed is:
1. A method comprises: receiving, by a plurality of storage units
of a dispersed storage network (DSN), updated properties of DSN
memory, wherein the DSN memory includes the plurality of storage
units and wherein the updated properties of the DSN memory requires
storage migration within the DSN memory; establishing, by a first
storage unit and a second storage unit of the plurality of storage
units, a migration pairing based on the updated properties of the
DSN memory and in accordance with a scoring function; establishing,
between the first and second storage units, a storage migration
mechanism for migrating storage of data between the first and
second storage units based on the updated properties of the DSN
memory; and while migrating the storage of data between the first
and second storage units in accordance with the storage migration
mechanism: receiving from a third device of the DSN, by the first
storage unit or the second storage unit, a data access request
regarding data that has been or will be migrated between the first
and second storage units; determining, by the first storage unit or
the second storage unit, status of the migrating the storage of
data between the first and second storage units; determining, by
the first storage unit or the second storage unit, which of the
first and second storage units is to process the data access
request based on the status to produce a determined storage unit
for processing of the data access request and a non-determined
storage unit; when the data access request was received from the
third device of the DSN by the determined storage unit: processing,
by the determined storage unit and independent of the
non-determined storage unit, the data access request; and sending,
by the determined storage unit, a data access response to the third
device of the DSN issuing the data access request; and when the
data access request was received from the third device of the DSN
by the non-determined storage unit: forwarding, by the
non-determined storage unit, the data access request to the
determined storage unit; receiving, by the determined storage unit,
the data access request forwarded from the non-determined storage
unit; processing, by the determined storage unit, the data access
request; and sending, by the determined storage unit and
independent of the non-determined storage unit, the data access
response to the third device of the DSN issuing the data access
request.
2. The method of claim 1, wherein the establishing the migration
pairing comprises: performing, by the first storage unit, the
scoring function using one or more properties of DSN access
information and one or more properties of non-updated properties of
the DSN memory to identify a range of DSN addresses affiliated with
the first storage unit; performing, by the second storage unit, the
scoring function using the one or more properties of DSN access
information and the one or more properties of non-updated
properties of the DSN memory to identify the range of DSN addresses
affiliated with the first storage unit; performing, by the first
storage unit, an updated scoring function using the one or more
properties of DSN access information and one or more properties of
the updated properties of the DSN memory to identify a range of DSN
addresses affiliated with the second storage unit; performing, by
the second storage unit, the updated scoring function using the one
or more properties of DSN access information and the one or more
properties of the updated properties of the DSN memory to identify
the range of DSN addresses affiliated with the second storage unit;
and establishing, by the first and second storage units, the
migration pairing based on the range of DSN addresses being
affiliated with the first storage unit based on the non-updated
properties of the DSN memory and the range of DSN addresses being
affiliated with the second storage unit based on the updated
properties of the DSN memory.
3. The method of claim 1, wherein the establishing the storage
migration mechanism comprises: identifying an address range to
migrate; identifying stored data having an address within the
address range to migrate; establishing a data migration list that
includes the identified stored data; establishing a data migration
pattern for migrating the identified stored data between the first
and second storage units; and updating the data migration list as
the identified stored data is migrated between the first and second
storage units.
4. The method of claim 3 further comprises: determining, based on
non-updated properties of the DSN memory, a source storage unit of
the first and second storage units; determining, based on the
updated properties of the DSN memory, a destination storage unit of
the first and second storage units; and sending the identified
stored data from the source storage unit to the destination storage
unit.
5. The method of claim 1, wherein the receiving the data access
request comprises: receiving the data access request by the first
storage unit when the data access request was created in accordance
with the updated properties of DSN memory; and receiving the data
access request by the second storage unit when the data access
request was created in accordance with non-updated properties of
DSN memory.
6. The method of claim 1 further comprises: when the data access
request is a read request: determining the status of the migrating
storage of data includes: accessing a migration list of data being
migrated between the first and second storage units; determining
whether a data object of the read request has been migrated based
on the migration list; when the data object has been migrated,
indicating the status as migrated to destination; and when the data
object has not been migrated, indicating the status as not migrated
to destination; determining the determined storage unit includes:
determining that the first storage unit is the determined storage
unit when the read request was created based on non-updated
properties of the DSN memory and the status is not migrated to
destination; determining that the second storage unit is the
determined storage unit when the read request was created based on
the non-updated properties of the DSN memory and the status is
migrated to destination; determining that the first storage unit is
the determined storage unit when the read request was created based
on the updated properties of the DSN memory and the status is not
migrated to destination; and determining that the second storage
unit is the determined storage unit when the read request was
created based on the updated properties of the DSN memory and the
status is migrated to destination.
7. The method of claim 1 further comprises: when the data access
request is a new write request for a data object: determining the
status of the migrating storage of data includes: when the first
and second storage units possess the updated properties of the DSN
memory, setting the status for the new write request as write to
destination; determining the determined storage unit includes: when
the status indicates write to destination, performing an updated
scoring function using one or more properties of the new write
request and one or more properties of the updated properties of the
DSN memory to identify the second storage unit as the determined
storage unit; processing the data access request includes: storing
the data object by the second storage unit; and updating a
migration list to include that the data object has been migrated to
the destination.
8. The method of claim 1 further comprises: when the data access
request is a revision write request for a revised data object:
determining the status of the migrating storage of data includes:
accessing a migration list of data being migrated between the first
and second storage units; determining whether a predetermined
number of data objects on the migration list have been migrated to
a destination; when the predetermined number of data objects have
been migrated, indicating the status as migrated to destination;
and when the predetermined number of data objects have not been
migrated, indicating the status as not migrated to destination;
determining the determined storage unit includes: when the status
indicates migrated to destination, identifying the second storage
unit as the destination and as the determined storage unit; and
when the status indicates not migrated to destination, identifying
the first storage unit as a source and as the determined storage
unit; processing the data access request includes: when the status
indicates migrated to destination: storing the revised data object
by the second storage unit; and updating the migration list to
include that the revised data object has been migrated to the
destination; and when the status indicates not migrated to
destination: storing the revised data object by the first storage
unit; and updating the migration list to include that the revised
data object has not been migrated to the destination.
9. A non-transitory computer readable storage medium comprises: at
least one memory section that stores operational instructions that,
when executed by one or more processing modules of one or more
computing devices of a dispersed storage network (DSN), causes the
one or more computing devices to: receive, by a plurality of
storage units of the DSN, updated properties of DSN memory, wherein
the DSN memory includes the plurality of storage units and wherein
the updated properties of the DSN memory requires storage migration
within the DSN memory; establish, by a first storage unit and a
second storage unit of the plurality of storage units, a migration
pairing based on the updated properties of the DSN memory and in
accordance with a scoring function; establish, between the first
and second storage units, a storage migration mechanism for
migrating storage of data between the first and second storage
units based on the updated properties of the DSN memory; and while
migrating the storage of data between the first and second storage
units in accordance with the storage migration mechanism: receive
from a third device of the DSN, by the first storage unit or the
second storage unit, a data access request regarding data that has
been or will be migrated between the first and second storage
units; determine, by the first storage unit or the second storage
unit, status of the migrating the storage of data between the first
and second storage units; determine, by the first storage unit or
the second storage unit, which of the first and second storage
units is to process the data access request based on the status to
produce a determined storage unit for processing of the data access
request and a non-determined storage unit; when the data access
request was received from the third device of the DSN by the
determined storage unit: process, by the determined storage unit,
the data access request; and send, by the determined storage unit,
a data access response to the third device of the DSN issuing the
data access request; and when the data access request was received
from the third device of the DSN by the non-determined storage
unit: forward, by the non-determined storage unit, the data access
request to the determined storage unit; receive, by the determined
storage unit, the data access request forwarded from the
non-determined storage unit; process, by the determined storage
unit, the data access request; and send, by the determined storage
unit and independent of the non-determined storage unit, the data
access response to the third device of the DSN issuing the data
access request.
10. The non-transitory computer readable storage medium of claim 9,
wherein the one or more processing modules functions to execute the
operational instructions stored by the at least one memory section
to cause the one or more computing devices of the DSN to establish
the migration pairing by: performing, by the first storage unit,
the scoring function using one or more properties of DSN access
information and one or more properties of non-updated properties of
the DSN memory to identify a range of DSN addresses affiliated with
the first storage unit; performing, by the second storage unit, the
scoring function using the one or more properties of DSN access
information and the one or more properties of non-updated
properties of the DSN memory to identify the range of DSN addresses
affiliated with the first storage unit; performing, by the first
storage unit, an updated scoring function using the one or more
properties of DSN access information and one or more properties of
the updated properties of the DSN memory to identify a range of DSN
addresses affiliated with the second storage unit; performing, by
the second storage unit, the updated scoring function using the one
or more properties of DSN access information and the one or more
properties of the updated properties of the DSN memory to identify
the range of DSN addresses affiliated with the second storage unit;
and establishing, by the first and second storage units, the
migration pairing based on the range of DSN addresses being
affiliated with the first storage unit based on the non-updated
properties of the DSN memory and the range of DSN addresses being
affiliated with the second storage unit based on the updated
properties of the DSN memory.
11. The non-transitory computer readable storage medium of claim 9,
wherein the one or more processing modules functions to execute the
operational instructions stored by the at least one memory section
to cause the one or more computing devices of the DSN to establish
the storage migration mechanism by: identifying an address range to
migrate; identifying stored data having an address within the
address range to migrate; establishing a data migration list that
includes the identified stored data; establishing a data migration
pattern for migrating the identified stored data between the first
and second storage units; and updating the data migration list as
the identified stored data is migrated between the first and second
storage units.
12. The non-transitory computer readable storage medium of claim 11
further comprises: the at least one memory section stores further
operational instructions that, when executed by the one or more
processing modules, causes the one or more computing devices of the
DSN to: determine, based on non-updated properties of the DSN
memory, a source storage unit of the first and second storage
units; determine, based on the updated properties of the DSN
memory, a destination storage unit of the first and second storage
units; and send the identified stored data from the source storage
unit to the destination storage unit.
13. The non-transitory computer readable storage medium of claim 9,
wherein the one or more processing modules functions to execute the
operational instructions stored by the at least one memory section
to cause the one or more computing devices of the DSN to receive
the data access request by: receiving the data access request by
the first storage unit when the data access request was created in
accordance with the updated properties of DSN memory; and receiving
the data access request by the second storage unit when the data
access request was created in accordance with non-updated
properties of DSN memory.
14. The non-transitory computer readable storage medium of claim 9
further comprises: the at least one memory section stores further
operational instructions that, when executed by the one or more
processing modules, causes the one or more computing devices of the
DSN to: when the data access request is a read request: determine
the status of the migrating storage of data includes: access a
migration list of data being migrated between the first and second
storage units; determine whether a data object of the read request
has been migrated based on the migration list; when the data object
has been migrated, indicate the status as migrated to destination;
and when the data object has not been migrated, indicate the status
as not migrated to destination; determine the determined storage
unit includes: determine that the first storage unit is the
determined storage unit when the read request was created based on
non-updated properties of the DSN memory and the status is not
migrated to destination; determine that the second storage unit is
the determined storage unit when the read request was created based
on the non-updated properties of the DSN memory and the status is
migrated to destination; determine that the first storage unit is
the determined storage unit when the read request was created based
on the updated properties of the DSN memory and the status is not
migrated to destination; and determine that the second storage unit
is the determined storage unit when the read request was created
based on the updated properties of the DSN memory and the status is
migrated to destination.
15. The non-transitory computer readable storage medium of claim 9
further comprises: the at least one memory section stores further
operational instructions that, when executed by the one or more
processing modules, causes the one or more computing devices of the
DSN to: when the data access request is a new write request for a
data object: determine the status of the migrating storage of data
includes: when the first and second storage units possess the
updated properties of the DSN memory, set the status for the new
write request as write to destination; determine the determined
storage unit includes: when the status indicates write to
destination, perform an updated scoring function using one or more
properties of the new write request and one or more properties of
the updated properties of the DSN memory to identify the second
storage unit as the determined storage unit; process the data
access request includes: store the data object by the second
storage unit; and update a migration list to include that the data
object has been migrated to the destination.
16. The non-transitory computer readable storage medium of claim 9
further comprises: the at least one memory section stores further
operational instructions that, when executed by the one or more
processing modules, causes the one or more computing devices of the
DSN to: when the data access request is a revision write request
for a revised data object: determine the status of the migrating
storage of data includes: access a migration list of data being
migrated between the first and second storage units; determine
whether a predetermined number of data objects on the migration
list have been migrated to a destination; when the predetermined
number of data objects have been migrated, indicate the status as
migrated to destination; and when the predetermined number of data
objects have not been migrated, indicate the status as not migrated
to destination; determine the determined storage unit includes:
when the status indicates migrated to destination, identify the
second storage unit as the destination and as the determined
storage unit; and when the status indicates not migrated to
destination, identify the first storage unit as a source and as the
determined storage unit; process the data access request includes:
when the status indicates migrated to destination: store the
revised data object by the second storage unit; and update the
migration list to include that the revised data object has been
migrated to the destination; and when the status indicates not
migrated to destination: store the revised data object by the first
storage unit; and update the migration list to include that the
revised data object has not been migrated to the destination.
Description
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
NOT APPLICABLE
INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT
DISC
NOT APPLICABLE
BACKGROUND OF THE INVENTION
Technical Field of the Invention
This invention relates generally to computer networks and more
particularly to dispersed storage of data and distributed task
processing of data.
Description of Related Art
Computing devices are known to communicate data, process data,
and/or store data. Such computing devices range from wireless smart
phones, laptops, tablets, personal computers (PC), work stations,
and video game devices, to data centers that support millions of
web searches, stock trades, or on-line purchases every day. In
general, a computing device includes a central processing unit
(CPU), a memory system, user input/output interfaces, peripheral
device interfaces, and an interconnecting bus structure.
As is further known, a computer may effectively extend its CPU by
using "cloud computing" to perform one or more computing functions
(e.g., a service, an application, an algorithm, an arithmetic logic
function, etc.) on behalf of the computer. Further, for large
services, applications, and/or functions, cloud computing may be
performed by multiple cloud computing resources in a distributed
manner to improve the response time for completion of the service,
application, and/or function. For example, Hadoop is an open source
software framework that supports distributed applications enabling
application execution by thousands of computers.
In addition to cloud computing, a computer may use "cloud storage"
as part of its memory system. As is known, cloud storage enables a
user, via its computer, to store files, applications, etc. on an
Internet storage system. The Internet storage system may include a
RAID (redundant array of independent disks) system and/or a
dispersed storage system that uses an error correction scheme to
encode data for storage.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)
FIG. 1 is a schematic block diagram of an embodiment of a
distributed computing system in accordance with the present
invention;
FIG. 2 is a schematic block diagram of an embodiment of a computing
core in accordance with the present invention;
FIG. 3 is a diagram of an example of a distributed storage and task
processing in accordance with the present invention;
FIG. 4 is a schematic block diagram of an embodiment of an outbound
distributed storage and/or task (DST) processing in accordance with
the present invention;
FIG. 5 is a logic diagram of an example of a method for outbound
DST processing in accordance with the present invention;
FIG. 6 is a schematic block diagram of an embodiment of a dispersed
error encoding in accordance with the present invention;
FIG. 7 is a diagram of an example of a segment processing of the
dispersed error encoding in accordance with the present
invention;
FIG. 8 is a diagram of an example of error encoding and slicing
processing of the dispersed error encoding in accordance with the
present invention;
FIG. 9 is a diagram of an example of grouping selection processing
of the outbound DST processing in accordance with the present
invention;
FIG. 10 is a diagram of an example of converting data into slice
groups in accordance with the present invention;
FIG. 11 is a schematic block diagram of an embodiment of a DST
execution unit in accordance with the present invention;
FIG. 12 is a schematic block diagram of an example of operation of
a DST execution unit in accordance with the present invention;
FIG. 13 is a schematic block diagram of an embodiment of an inbound
distributed storage and/or task (DST) processing in accordance with
the present invention;
FIG. 14 is a logic diagram of an example of a method for inbound
DST processing in accordance with the present invention;
FIG. 15 is a diagram of an example of de-grouping selection
processing of the inbound DST processing in accordance with the
present invention;
FIG. 16 is a schematic block diagram of an embodiment of a
dispersed error decoding in accordance with the present
invention;
FIG. 17 is a diagram of an example of de-slicing and error decoding
processing of the dispersed error decoding in accordance with the
present invention;
FIG. 18 is a diagram of an example of a de-segment processing of
the dispersed error decoding in accordance with the present
invention;
FIG. 19 is a diagram of an example of converting slice groups into
data in accordance with the present invention;
FIG. 20 is a diagram of an example of a distributed storage within
the distributed computing system in accordance with the present
invention;
FIG. 21 is a schematic block diagram of an example of operation of
outbound distributed storage and/or task (DST) processing for
storing data in accordance with the present invention;
FIG. 22 is a schematic block diagram of an example of a dispersed
error encoding for the example of FIG. 21 in accordance with the
present invention;
FIG. 23 is a diagram of an example of converting data into pillar
slice groups for storage in accordance with the present
invention;
FIG. 24 is a schematic block diagram of an example of a storage
operation of a DST execution unit in accordance with the present
invention;
FIG. 25 is a schematic block diagram of an example of operation of
inbound distributed storage and/or task (DST) processing for
retrieving dispersed error encoded data in accordance with the
present invention;
FIG. 26 is a schematic block diagram of an example of a dispersed
error decoding for the example of FIG. 25 in accordance with the
present invention;
FIG. 27 is a schematic block diagram of an example of a distributed
storage and task processing network (DSTN) module storing a
plurality of data and a plurality of task codes in accordance with
the present invention;
FIG. 28 is a schematic block diagram of an example of the
distributed computing system performing tasks on stored data in
accordance with the present invention;
FIG. 29 is a schematic block diagram of an embodiment of a task
distribution module facilitating the example of FIG. 28 in
accordance with the present invention;
FIG. 30 is a diagram of a specific example of the distributed
computing system performing tasks on stored data in accordance with
the present invention;
FIG. 31 is a schematic block diagram of an example of a distributed
storage and task processing network (DSTN) module storing data and
task codes for the example of FIG. 30 in accordance with the
present invention;
FIG. 32 is a diagram of an example of DST allocation information
for the example of FIG. 30 in accordance with the present
invention;
FIGS. 33-38 are schematic block diagrams of the DSTN module
performing the example of FIG. 30 in accordance with the present
invention;
FIG. 39 is a diagram of an example of combining result information
into final results for the example of FIG. 30 in accordance with
the present invention;
FIG. 40A is a schematic block diagram of an embodiment of a
decentralized agreement module in accordance with the present
invention;
FIG. 40B is a flowchart illustrating an example of selecting the
resource in accordance with the present invention;
FIG. 40C is a schematic block diagram of an embodiment of a
dispersed storage network (DSN) in accordance with the present
invention;
FIG. 40D is a flowchart illustrating an example of accessing a
dispersed storage network (DSN) memory in accordance with the
present invention;
FIG. 41A is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) in accordance with the present
invention;
FIG. 41B is a flowchart illustrating an example of accessing and
rebuilding encoded data slices in accordance with the present
invention;
FIG. 42A is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) in accordance with the present
invention;
FIG. 42B is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) in accordance with the present
invention;
FIG. 42C is a flowchart illustrating an example of selecting
storage resources in accordance with the present invention;
FIG. 43A is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) in accordance with the present
invention;
FIG. 43B is a flowchart illustrating another example of selecting
storage resources slices in accordance with the present
invention;
FIG. 44A is a schematic block diagram of another embodiment of a
distributed storage and task (DST) execution (EX) unit in
accordance with the present invention;
FIG. 44B is a flowchart illustrating an example of de-marking
encoded data slices in accordance with the present invention;
FIGS. 45A-45E are a schematic block diagram of another embodiment
of a dispersed storage network (DSN) in accordance with the present
invention;
FIG. 45F is a flowchart illustrating an example of accessing data
while migrating storage of the data in accordance with the present
invention;
FIG. 46A is a schematic block diagram of another embodiment of a
distributed storage and task network (DSTN) in accordance with the
present invention;
FIG. 46B is a flowchart illustrating an example of selecting task
execution resources in accordance with the present invention;
FIG. 47A is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) in accordance with the present
invention;
FIG. 47B is a flowchart illustrating an example of updating storage
unit configuration information in accordance with the present
invention;
FIG. 48A is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) in accordance with the present
invention;
FIG. 48B is a flowchart illustrating another example of migrating
slices in accordance with the present invention;
FIG. 49A is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) in accordance with the present
invention; and
FIG. 49B is a flowchart illustrating another example of migrating
slices in accordance with the present invention.
DETAILED DESCRIPTION OF THE INVENTION
FIG. 1 is a schematic block diagram of an embodiment of a
distributed computing system 10 that includes a user device 12
and/or a user device 14, a distributed storage and/or task (DST)
processing unit 16, a distributed storage and/or task network
(DSTN) managing unit 18, a DST integrity processing unit 20, and a
distributed storage and/or task network (DSTN) module 22. The
components of the distributed computing system 10 are coupled via a
network 24, which may include one or more wireless and/or wire
lined communication systems; one or more private intranet systems
and/or public internet systems; and/or one or more local area
networks (LAN) and/or wide area networks (WAN).
The DSTN module 22 includes a plurality of distributed storage
and/or task (DST) execution units 36 that may be located at
geographically different sites (e.g., one in Chicago, one in
Milwaukee, etc.). Each of the DST execution units is operable to
store dispersed error encoded data and/or to execute, in a
distributed manner, one or more tasks on data. The tasks may be a
simple function (e.g., a mathematical function, a logic function,
an identify function, a find function, a search engine function, a
replace function, etc.), a complex function (e.g., compression,
human and/or computer language translation, text-to-voice
conversion, voice-to-text conversion, etc.), multiple simple and/or
complex functions, one or more algorithms, one or more
applications, etc.
Each of the user devices 12-14, the DST processing unit 16, the
DSTN managing unit 18, and the DST integrity processing unit 20
include a computing core 26 and may be a portable computing device
and/or a fixed computing device. A portable computing device may be
a social networking device, a gaming device, a cell phone, a smart
phone, a personal digital assistant, a digital music player, a
digital video player, a laptop computer, a handheld computer, a
tablet, a video game controller, and/or any other portable device
that includes a computing core. A fixed computing device may be a
personal computer (PC), a computer server, a cable set-top box, a
satellite receiver, a television set, a printer, a fax machine,
home entertainment equipment, a video game console, and/or any type
of home or office computing equipment. User device 12 and DST
processing unit 16 are configured to include a DST client module
34.
With respect to interfaces, each interface 30, 32, and 33 includes
software and/or hardware to support one or more communication links
via the network 24 indirectly and/or directly. For example,
interface 30 supports a communication link (e.g., wired, wireless,
direct, via a LAN, via the network 24, etc.) between user device 14
and the DST processing unit 16. As another example, interface 32
supports communication links (e.g., a wired connection, a wireless
connection, a LAN connection, and/or any other type of connection
to/from the network 24) between user device 12 and the DSTN module
22 and between the DST processing unit 16 and the DSTN module 22.
As yet another example, interface 33 supports a communication link
for each of the DSTN managing unit 18 and DST integrity processing
unit 20 to the network 24.
The distributed computing system 10 is operable to support
dispersed storage (DS) error encoded data storage and retrieval, to
support distributed task processing on received data, and/or to
support distributed task processing on stored data. In general and
with respect to DS error encoded data storage and retrieval, the
distributed computing system 10 supports three primary operations:
storage management, data storage and retrieval (an example of which
will be discussed with reference to FIGS. 20-26), and data storage
integrity verification. In accordance with these three primary
functions, data can be encoded, distributedly stored in physically
different locations, and subsequently retrieved in a reliable and
secure manner. Such a system is tolerant of a significant number of
failures (e.g., up to a failure level, which may be greater than or
equal to a pillar width minus a decode threshold minus one) that
may result from individual storage device failures and/or network
equipment failures without loss of data and without the need for a
redundant or backup copy. Further, the system allows the data to be
stored for an indefinite period of time without data loss and does
so in a secure manner (e.g., the system is very resistant to
attempts at hacking the data).
The second primary function (i.e., distributed data storage and
retrieval) begins and ends with a user device 12-14. For instance,
if a second type of user device 14 has data 40 to store in the DSTN
module 22, it sends the data 40 to the DST processing unit 16 via
its interface 30. The interface 30 functions to mimic a
conventional operating system (OS) file system interface (e.g.,
network file system (NFS), flash file system (FFS), disk file
system (DFS), file transfer protocol (FTP), web-based distributed
authoring and versioning (WebDAV), etc.) and/or a block memory
interface (e.g., small computer system interface (SCSI), internet
small computer system interface (iSCSI), etc.). In addition, the
interface 30 may attach a user identification code (ID) to the data
40.
To support storage management, the DSTN managing unit 18 performs
DS management services. One such DS management service includes the
DSTN managing unit 18 establishing distributed data storage
parameters (e.g., vault creation, distributed storage parameters,
security parameters, billing information, user profile information,
etc.) for a user device 12-14 individually or as part of a group of
user devices. For example, the DSTN managing unit 18 coordinates
creation of a vault (e.g., a virtual memory block) within memory of
the DSTN module 22 for a user device, a group of devices, or for
public access and establishes per vault dispersed storage (DS)
error encoding parameters for a vault. The DSTN managing unit 18
may facilitate storage of DS error encoding parameters for each
vault of a plurality of vaults by updating registry information for
the distributed computing system 10. The facilitating includes
storing updated registry information in one or more of the DSTN
module 22, the user device 12, the DST processing unit 16, and the
DST integrity processing unit 20.
The DS error encoding parameters (e.g., or dispersed storage error
coding parameters) include data segmenting information (e.g., how
many segments data (e.g., a file, a group of files, a data block,
etc.) is divided into), segment security information (e.g., per
segment encryption, compression, integrity checksum, etc.), error
coding information (e.g., pillar width, decode threshold, read
threshold, write threshold, etc.), slicing information (e.g., the
number of encoded data slices that will be created for each data
segment); and slice security information (e.g., per encoded data
slice encryption, compression, integrity checksum, etc.).
The DSTN managing unit 18 creates and stores user profile
information (e.g., an access control list (ACL)) in local memory
and/or within memory of the DSTN module 22. The user profile
information includes authentication information, permissions,
and/or the security parameters. The security parameters may include
encryption/decryption scheme, one or more encryption keys, key
generation scheme, and/or data encoding/decoding scheme.
The DSTN managing unit 18 creates billing information for a
particular user, a user group, a vault access, public vault access,
etc. For instance, the DSTN managing unit 18 tracks the number of
times a user accesses a private vault and/or public vaults, which
can be used to generate a per-access billing information. In
another instance, the DSTN managing unit 18 tracks the amount of
data stored and/or retrieved by a user device and/or a user group,
which can be used to generate a per-data-amount billing
information.
Another DS management service includes the DSTN managing unit 18
performing network operations, network administration, and/or
network maintenance. Network operations includes authenticating
user data allocation requests (e.g., read and/or write requests),
managing creation of vaults, establishing authentication
credentials for user devices, adding/deleting components (e.g.,
user devices, DST execution units, and/or DST processing units)
from the distributed computing system 10, and/or establishing
authentication credentials for DST execution units 36. Network
administration includes monitoring devices and/or units for
failures, maintaining vault information, determining device and/or
unit activation status, determining device and/or unit loading,
and/or determining any other system level operation that affects
the performance level of the system 10. Network maintenance
includes facilitating replacing, upgrading, repairing, and/or
expanding a device and/or unit of the system 10.
To support data storage integrity verification within the
distributed computing system 10, the DST integrity processing unit
20 performs rebuilding of `bad` or missing encoded data slices. At
a high level, the DST integrity processing unit 20 performs
rebuilding by periodically attempting to retrieve/list encoded data
slices, and/or slice names of the encoded data slices, from the
DSTN module 22. For retrieved encoded slices, they are checked for
errors due to data corruption, outdated version, etc. If a slice
includes an error, it is flagged as a `bad` slice. For encoded data
slices that were not received and/or not listed, they are flagged
as missing slices. Bad and/or missing slices are subsequently
rebuilt using other retrieved encoded data slices that are deemed
to be good slices to produce rebuilt slices. The rebuilt slices are
stored in memory of the DSTN module 22. Note that the DST integrity
processing unit 20 may be a separate unit as shown, it may be
included in the DSTN module 22, it may be included in the DST
processing unit 16, and/or distributed among the DST execution
units 36.
To support distributed task processing on received data, the
distributed computing system 10 has two primary operations: DST
(distributed storage and/or task processing) management and DST
execution on received data (an example of which will be discussed
with reference to FIGS. 3-19). With respect to the storage portion
of the DST management, the DSTN managing unit 18 functions as
previously described. With respect to the tasking processing of the
DST management, the DSTN managing unit 18 performs distributed task
processing (DTP) management services. One such DTP management
service includes the DSTN managing unit 18 establishing DTP
parameters (e.g., user-vault affiliation information, billing
information, user-task information, etc.) for a user device 12-14
individually or as part of a group of user devices.
Another DTP management service includes the DSTN managing unit 18
performing DTP network operations, network administration (which is
essentially the same as described above), and/or network
maintenance (which is essentially the same as described above).
Network operations include, but are not limited to, authenticating
user task processing requests (e.g., valid request, valid user,
etc.), authenticating results and/or partial results, establishing
DTP authentication credentials for user devices, adding/deleting
components (e.g., user devices, DST execution units, and/or DST
processing units) from the distributed computing system, and/or
establishing DTP authentication credentials for DST execution
units.
To support distributed task processing on stored data, the
distributed computing system 10 has two primary operations: DST
(distributed storage and/or task) management and DST execution on
stored data. With respect to the DST execution on stored data, if
the second type of user device 14 has a task request 38 for
execution by the DSTN module 22, it sends the task request 38 to
the DST processing unit 16 via its interface 30. An example of DST
execution on stored data will be discussed in greater detail with
reference to FIGS. 27-39. With respect to the DST management, it is
substantially similar to the DST management to support distributed
task processing on received data.
FIG. 2 is a schematic block diagram of an embodiment of a computing
core 26 that includes a processing module 50, a memory controller
52, main memory 54, a video graphics processing unit 55, an
input/output (IO) controller 56, a peripheral component
interconnect (PCI) interface 58, an IO interface module 60, at
least one IO device interface module 62, a read only memory (ROM)
basic input output system (BIOS) 64, and one or more memory
interface modules. The one or more memory interface module(s)
includes one or more of a universal serial bus (USB) interface
module 66, a host bus adapter (HBA) interface module 68, a network
interface module 70, a flash interface module 72, a hard drive
interface module 74, and a DSTN interface module 76.
The DSTN interface module 76 functions to mimic a conventional
operating system (OS) file system interface (e.g., network file
system (NFS), flash file system (FFS), disk file system (DFS), file
transfer protocol (FTP), web-based distributed authoring and
versioning (WebDAV), etc.) and/or a block memory interface (e.g.,
small computer system interface (SCSI), internet small computer
system interface (iSCSI), etc.). The DSTN interface module 76
and/or the network interface module 70 may function as the
interface 30 of the user device 14 of FIG. 1. Further note that the
IO device interface module 62 and/or the memory interface modules
may be collectively or individually referred to as IO ports.
FIG. 3 is a diagram of an example of the distributed computing
system performing a distributed storage and task processing
operation. The distributed computing system includes a DST
(distributed storage and/or task) client module 34 (which may be in
user device 14 and/or in DST processing unit 16 of FIG. 1), a
network 24, a plurality of DST execution units 1-n that includes
two or more DST execution units 36 of FIG. 1 (which form at least a
portion of DSTN module 22 of FIG. 1), a DST managing module (not
shown), and a DST integrity verification module (not shown). The
DST client module 34 includes an outbound DST processing section 80
and an inbound DST processing section 82. Each of the DST execution
units 1-n includes a controller 86, a processing module 84, memory
88, a DT (distributed task) execution module 90, and a DST client
module 34.
In an example of operation, the DST client module 34 receives data
92 and one or more tasks 94 to be performed upon the data 92. The
data 92 may be of any size and of any content, where, due to the
size (e.g., greater than a few Terabytes), the content (e.g.,
secure data, etc.), and/or task(s) (e.g., MIPS intensive),
distributed processing of the task(s) on the data is desired. For
example, the data 92 may be one or more digital books, a copy of a
company's emails, a large-scale Internet search, a video security
file, one or more entertainment video files (e.g., television
programs, movies, etc.), data files, and/or any other large amount
of data (e.g., greater than a few Terabytes).
Within the DST client module 34, the outbound DST processing
section 80 receives the data 92 and the task(s) 94. The outbound
DST processing section 80 processes the data 92 to produce slice
groupings 96. As an example of such processing, the outbound DST
processing section 80 partitions the data 92 into a plurality of
data partitions. For each data partition, the outbound DST
processing section 80 dispersed storage (DS) error encodes the data
partition to produce encoded data slices and groups the encoded
data slices into a slice grouping 96. In addition, the outbound DST
processing section 80 partitions the task 94 into partial tasks 98,
where the number of partial tasks 98 may correspond to the number
of slice groupings 96.
The outbound DST processing section 80 then sends, via the network
24, the slice groupings 96 and the partial tasks 98 to the DST
execution units 1-n of the DSTN module 22 of FIG. 1. For example,
the outbound DST processing section 80 sends slice group 1 and
partial task 1 to DST execution unit 1. As another example, the
outbound DST processing section 80 sends slice group #n and partial
task #n to DST execution unit #n.
Each DST execution unit performs its partial task 98 upon its slice
group 96 to produce partial results 102. For example, DST execution
unit #1 performs partial task #1 on slice group #1 to produce a
partial result #1, for results. As a more specific example, slice
group #1 corresponds to a data partition of a series of digital
books and the partial task #1 corresponds to searching for specific
phrases, recording where the phrase is found, and establishing a
phrase count. In this more specific example, the partial result #1
includes information as to where the phrase was found and includes
the phrase count.
Upon completion of generating their respective partial results 102,
the DST execution units send, via the network 24, their partial
results 102 to the inbound DST processing section 82 of the DST
client module 34. The inbound DST processing section 82 processes
the received partial results 102 to produce a result 104.
Continuing with the specific example of the preceding paragraph,
the inbound DST processing section 82 combines the phrase count
from each of the DST execution units 36 to produce a total phrase
count. In addition, the inbound DST processing section 82 combines
the `where the phrase was found` information from each of the DST
execution units 36 within their respective data partitions to
produce `where the phrase was found` information for the series of
digital books.
In another example of operation, the DST client module 34 requests
retrieval of stored data within the memory of the DST execution
units 36 (e.g., memory of the DSTN module). In this example, the
task 94 is retrieve data stored in the memory of the DSTN module.
Accordingly, the outbound DST processing section 80 converts the
task 94 into a plurality of partial tasks 98 and sends the partial
tasks 98 to the respective DST execution units 1-n.
In response to the partial task 98 of retrieving stored data, a DST
execution unit 36 identifies the corresponding encoded data slices
100 and retrieves them. For example, DST execution unit #1 receives
partial task #1 and retrieves, in response thereto, retrieved
slices #1. The DST execution units 36 send their respective
retrieved slices 100 to the inbound DST processing section 82 via
the network 24.
The inbound DST processing section 82 converts the retrieved slices
100 into data 92. For example, the inbound DST processing section
82 de-groups the retrieved slices 100 to produce encoded slices per
data partition. The inbound DST processing section 82 then DS error
decodes the encoded slices per data partition to produce data
partitions. The inbound DST processing section 82 de-partitions the
data partitions to recapture the data 92.
FIG. 4 is a schematic block diagram of an embodiment of an outbound
distributed storage and/or task (DST) processing section 80 of a
DST client module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1
(e.g., a plurality of n DST execution units 36) via a network 24.
The outbound DST processing section 80 includes a data partitioning
module 110, a dispersed storage (DS) error encoding module 112, a
grouping selector module 114, a control module 116, and a
distributed task control module 118.
In an example of operation, the data partitioning module 110
partitions data 92 into a plurality of data partitions 120. The
number of partitions and the size of the partitions may be selected
by the control module 116 via control 160 based on the data 92
(e.g., its size, its content, etc.), a corresponding task 94 to be
performed (e.g., simple, complex, single step, multiple steps,
etc.), DS encoding parameters (e.g., pillar width, decode
threshold, write threshold, segment security parameters, slice
security parameters, etc.), capabilities of the DST execution units
36 (e.g., processing resources, availability of processing
recourses, etc.), and/or as may be inputted by a user, system
administrator, or other operator (human or automated). For example,
the data partitioning module 110 partitions the data 92 (e.g., 100
Terabytes) into 100,000 data segments, each being 1 Gigabyte in
size. Alternatively, the data partitioning module 110 partitions
the data 92 into a plurality of data segments, where some of data
segments are of a different size, are of the same size, or a
combination thereof.
The DS error encoding module 112 receives the data partitions 120
in a serial manner, a parallel manner, and/or a combination
thereof. For each data partition 120, the DS error encoding module
112 DS error encodes the data partition 120 in accordance with
control information 160 from the control module 116 to produce
encoded data slices 122. The DS error encoding includes segmenting
the data partition into data segments, segment security processing
(e.g., encryption, compression, watermarking, integrity check
(e.g., CRC), etc.), error encoding, slicing, and/or per slice
security processing (e.g., encryption, compression, watermarking,
integrity check (e.g., CRC), etc.). The control information 160
indicates which steps of the DS error encoding are active for a
given data partition and, for active steps, indicates the
parameters for the step. For example, the control information 160
indicates that the error encoding is active and includes error
encoding parameters (e.g., pillar width, decode threshold, write
threshold, read threshold, type of error encoding, etc.).
The grouping selector module 114 groups the encoded slices 122 of a
data partition into a set of slice groupings 96. The number of
slice groupings corresponds to the number of DST execution units 36
identified for a particular task 94. For example, if five DST
execution units 36 are identified for the particular task 94, the
grouping selector module groups the encoded slices 122 of a data
partition into five slice groupings 96. The grouping selector
module 114 outputs the slice groupings 96 to the corresponding DST
execution units 36 via the network 24.
The distributed task control module 118 receives the task 94 and
converts the task 94 into a set of partial tasks 98. For example,
the distributed task control module 118 receives a task to find
where in the data (e.g., a series of books) a phrase occurs and a
total count of the phrase usage in the data. In this example, the
distributed task control module 118 replicates the task 94 for each
DST execution unit 36 to produce the partial tasks 98. In another
example, the distributed task control module 118 receives a task to
find where in the data a first phrase occurs, where in the data a
second phrase occurs, and a total count for each phrase usage in
the data. In this example, the distributed task control module 118
generates a first set of partial tasks 98 for finding and counting
the first phrase and a second set of partial tasks for finding and
counting the second phrase. The distributed task control module 118
sends respective first and/or second partial tasks 98 to each DST
execution unit 36.
FIG. 5 is a logic diagram of an example of a method for outbound
distributed storage and task (DST) processing that begins at step
126 where a DST client module receives data and one or more
corresponding tasks. The method continues at step 128 where the DST
client module determines a number of DST units to support the task
for one or more data partitions. For example, the DST client module
may determine the number of DST units to support the task based on
the size of the data, the requested task, the content of the data,
a predetermined number (e.g., user indicated, system administrator
determined, etc.), available DST units, capability of the DST
units, and/or any other factor regarding distributed task
processing of the data. The DST client module may select the same
DST units for each data partition, may select different DST units
for the data partitions, or a combination thereof.
The method continues at step 130 where the DST client module
determines processing parameters of the data based on the number of
DST units selected for distributed task processing. The processing
parameters include data partitioning information, DS encoding
parameters, and/or slice grouping information. The data
partitioning information includes a number of data partitions, size
of each data partition, and/or organization of the data partitions
(e.g., number of data blocks in a partition, the size of the data
blocks, and arrangement of the data blocks). The DS encoding
parameters include segmenting information, segment security
information, error encoding information (e.g., dispersed storage
error encoding function parameters including one or more of pillar
width, decode threshold, write threshold, read threshold, generator
matrix), slicing information, and/or per slice security
information. The slice grouping information includes information
regarding how to arrange the encoded data slices into groups for
the selected DST units. As a specific example, if the DST client
module determines that five DST units are needed to support the
task, then it determines that the error encoding parameters include
a pillar width of five and a decode threshold of three.
The method continues at step 132 where the DST client module
determines task partitioning information (e.g., how to partition
the tasks) based on the selected DST units and data processing
parameters. The data processing parameters include the processing
parameters and DST unit capability information. The DST unit
capability information includes the number of DT (distributed task)
execution units, execution capabilities of each DT execution unit
(e.g., MIPS capabilities, processing resources (e.g., quantity and
capability of microprocessors, CPUs, digital signal processors,
co-processor, microcontrollers, arithmetic logic circuitry, and/or
any other analog and/or digital processing circuitry), availability
of the processing resources, memory information (e.g., type, size,
availability, etc.)), and/or any information germane to executing
one or more tasks.
The method continues at step 134 where the DST client module
processes the data in accordance with the processing parameters to
produce slice groupings. The method continues at step 136 where the
DST client module partitions the task based on the task
partitioning information to produce a set of partial tasks. The
method continues at step 138 where the DST client module sends the
slice groupings and the corresponding partial tasks to respective
DST units.
FIG. 6 is a schematic block diagram of an embodiment of the
dispersed storage (DS) error encoding module 112 of an outbound
distributed storage and task (DST) processing section. The DS error
encoding module 112 includes a segment processing module 142, a
segment security processing module 144, an error encoding module
146, a slicing module 148, and a per slice security processing
module 150. Each of these modules is coupled to a control module
116 to receive control information 160 therefrom.
In an example of operation, the segment processing module 142
receives a data partition 120 from a data partitioning module and
receives segmenting information as the control information 160 from
the control module 116. The segmenting information indicates how
the segment processing module 142 is to segment the data partition
120. For example, the segmenting information indicates how many
rows to segment the data based on a decode threshold of an error
encoding scheme, indicates how many columns to segment the data
into based on a number and size of data blocks within the data
partition 120, and indicates how many columns to include in a data
segment 152. The segment processing module 142 segments the data
120 into data segments 152 in accordance with the segmenting
information.
The segment security processing module 144, when enabled by the
control module 116, secures the data segments 152 based on segment
security information received as control information 160 from the
control module 116. The segment security information includes data
compression, encryption, watermarking, integrity check (e.g.,
cyclic redundancy check (CRC), etc.), and/or any other type of
digital security. For example, when the segment security processing
module 144 is enabled, it may compress a data segment 152, encrypt
the compressed data segment, and generate a CRC value for the
encrypted data segment to produce a secure data segment 154. When
the segment security processing module 144 is not enabled, it
passes the data segments 152 to the error encoding module 146 or is
bypassed such that the data segments 152 are provided to the error
encoding module 146.
The error encoding module 146 encodes the secure data segments 154
in accordance with error correction encoding parameters received as
control information 160 from the control module 116. The error
correction encoding parameters (e.g., also referred to as dispersed
storage error coding parameters) include identifying an error
correction encoding scheme (e.g., forward error correction
algorithm, a Reed-Solomon based algorithm, an online coding
algorithm, an information dispersal algorithm, etc.), a pillar
width, a decode threshold, a read threshold, a write threshold,
etc. For example, the error correction encoding parameters identify
a specific error correction encoding scheme, specifies a pillar
width of five, and specifies a decode threshold of three. From
these parameters, the error encoding module 146 encodes a data
segment 154 to produce an encoded data segment 156.
The slicing module 148 slices the encoded data segment 156 in
accordance with the pillar width of the error correction encoding
parameters received as control information 160. For example, if the
pillar width is five, the slicing module 148 slices an encoded data
segment 156 into a set of five encoded data slices. As such, for a
plurality of encoded data segments 156 for a given data partition,
the slicing module outputs a plurality of sets of encoded data
slices 158.
The per slice security processing module 150, when enabled by the
control module 116, secures each encoded data slice 158 based on
slice security information received as control information 160 from
the control module 116. The slice security information includes
data compression, encryption, watermarking, integrity check (e.g.,
CRC, etc.), and/or any other type of digital security. For example,
when the per slice security processing module 150 is enabled, it
compresses an encoded data slice 158, encrypts the compressed
encoded data slice, and generates a CRC value for the encrypted
encoded data slice to produce a secure encoded data slice 122. When
the per slice security processing module 150 is not enabled, it
passes the encoded data slices 158 or is bypassed such that the
encoded data slices 158 are the output of the DS error encoding
module 112. Note that the control module 116 may be omitted and
each module stores its own parameters.
FIG. 7 is a diagram of an example of a segment processing of a
dispersed storage (DS) error encoding module. In this example, a
segment processing module 142 receives a data partition 120 that
includes 45 data blocks (e.g., d1-d45), receives segmenting
information (i.e., control information 160) from a control module,
and segments the data partition 120 in accordance with the control
information 160 to produce data segments 152. Each data block may
be of the same size as other data blocks or of a different size. In
addition, the size of each data block may be a few bytes to
megabytes of data. As previously mentioned, the segmenting
information indicates how many rows to segment the data partition
into, indicates how many columns to segment the data partition
into, and indicates how many columns to include in a data
segment.
In this example, the decode threshold of the error encoding scheme
is three; as such the number of rows to divide the data partition
into is three. The number of columns for each row is set to 15,
which is based on the number and size of data blocks. The data
blocks of the data partition are arranged in rows and columns in a
sequential order (i.e., the first row includes the first 15 data
blocks; the second row includes the second 15 data blocks; and the
third row includes the last 15 data blocks).
With the data blocks arranged into the desired sequential order,
they are divided into data segments based on the segmenting
information. In this example, the data partition is divided into 8
data segments; the first 7 include 2 columns of three rows and the
last includes 1 column of three rows. Note that the first row of
the 8 data segments is in sequential order of the first 15 data
blocks; the second row of the 8 data segments in sequential order
of the second 15 data blocks; and the third row of the 8 data
segments in sequential order of the last 15 data blocks. Note that
the number of data blocks, the grouping of the data blocks into
segments, and size of the data blocks may vary to accommodate the
desired distributed task processing function.
FIG. 8 is a diagram of an example of error encoding and slicing
processing of the dispersed error encoding processing the data
segments of FIG. 7. In this example, data segment 1 includes 3 rows
with each row being treated as one word for encoding. As such, data
segment 1 includes three words for encoding: word 1 including data
blocks d1 and d2, word 2 including data blocks d16 and d17, and
word 3 including data blocks d31 and d32. Each of data segments 2-7
includes three words where each word includes two data blocks. Data
segment 8 includes three words where each word includes a single
data block (e.g., d15, d30, and d45).
In operation, an error encoding module 146 and a slicing module 148
convert each data segment into a set of encoded data slices in
accordance with error correction encoding parameters as control
information 160. More specifically, when the error correction
encoding parameters indicate a unity matrix Reed-Solomon based
encoding algorithm, 5 pillars, and decode threshold of 3, the first
three encoded data slices of the set of encoded data slices for a
data segment are substantially similar to the corresponding word of
the data segment. For instance, when the unity matrix Reed-Solomon
based encoding algorithm is applied to data segment 1, the content
of the first encoded data slice (DS1_d1&2) of the first set of
encoded data slices (e.g., corresponding to data segment 1) is
substantially similar to content of the first word (e.g., d1 &
d2); the content of the second encoded data slice (DS1_d16&17)
of the first set of encoded data slices is substantially similar to
content of the second word (e.g., d16 & d17); and the content
of the third encoded data slice (DS1_d31&32) of the first set
of encoded data slices is substantially similar to content of the
third word (e.g., d31 & d32).
The content of the fourth and fifth encoded data slices (e.g.,
ES1_1 and ES1_2) of the first set of encoded data slices include
error correction data based on the first-third words of the first
data segment. With such an encoding and slicing scheme, retrieving
any three of the five encoded data slices allows the data segment
to be accurately reconstructed.
The encoding and slicing of data segments 2-7 yield sets of encoded
data slices similar to the set of encoded data slices of data
segment 1. For instance, the content of the first encoded data
slice (DS2_d3&4) of the second set of encoded data slices
(e.g., corresponding to data segment 2) is substantially similar to
content of the first word (e.g., d3 & d4); the content of the
second encoded data slice (DS2_d18&19) of the second set of
encoded data slices is substantially similar to content of the
second word (e.g., d18 & d19); and the content of the third
encoded data slice (DS2_d33&34) of the second set of encoded
data slices is substantially similar to content of the third word
(e.g., d33 & d34). The content of the fourth and fifth encoded
data slices (e.g., ES1_1 and ES1_2) of the second set of encoded
data slices includes error correction data based on the first-third
words of the second data segment.
FIG. 9 is a diagram of an example of grouping selection processing
of an outbound distributed storage and task (DST) processing in
accordance with group selection information as control information
160 from a control module. Encoded slices for data partition 122
are grouped in accordance with the control information 160 to
produce slice groupings 96. In this example, a grouping selector
module 114 organizes the encoded data slices into five slice
groupings (e.g., one for each DST execution unit of a distributed
storage and task network (DSTN) module). As a specific example, the
grouping selector module 114 creates a first slice grouping for a
DST execution unit #1, which includes first encoded slices of each
of the sets of encoded slices. As such, the first DST execution
unit receives encoded data slices corresponding to data blocks 1-15
(e.g., encoded data slices of contiguous data).
The grouping selector module 114 also creates a second slice
grouping for a DST execution unit #2, which includes second encoded
slices of each of the sets of encoded slices. As such, the second
DST execution unit receives encoded data slices corresponding to
data blocks 16-30. The grouping selector module 114 further creates
a third slice grouping for DST execution unit #3, which includes
third encoded slices of each of the sets of encoded slices. As
such, the third DST execution unit receives encoded data slices
corresponding to data blocks 31-45.
The grouping selector module 114 creates a fourth slice grouping
for DST execution unit #4, which includes fourth encoded slices of
each of the sets of encoded slices. As such, the fourth DST
execution unit receives encoded data slices corresponding to first
error encoding information (e.g., encoded data slices of error
coding (EC) data). The grouping selector module 114 further creates
a fifth slice grouping for DST execution unit #5, which includes
fifth encoded slices of each of the sets of encoded slices. As
such, the fifth DST execution unit receives encoded data slices
corresponding to second error encoding information.
FIG. 10 is a diagram of an example of converting data 92 into slice
groups that expands on the preceding figures. As shown, the data 92
is partitioned in accordance with a partitioning function 164 into
a plurality of data partitions (1-x, where x is an integer greater
than 4). Each data partition (or chunkset of data) is encoded and
grouped into slice groupings as previously discussed by an encoding
and grouping function 166. For a given data partition, the slice
groupings are sent to distributed storage and task (DST) execution
units. From data partition to data partition, the ordering of the
slice groupings to the DST execution units may vary.
For example, the slice groupings of data partition #1 is sent to
the DST execution units such that the first DST execution receives
first encoded data slices of each of the sets of encoded data
slices, which corresponds to a first continuous data chunk of the
first data partition (e.g., refer to FIG. 9), a second DST
execution receives second encoded data slices of each of the sets
of encoded data slices, which corresponds to a second continuous
data chunk of the first data partition, etc.
For the second data partition, the slice groupings may be sent to
the DST execution units in a different order than it was done for
the first data partition. For instance, the first slice grouping of
the second data partition (e.g., slice group 2_1) is sent to the
second DST execution unit; the second slice grouping of the second
data partition (e.g., slice group 2_2) is sent to the third DST
execution unit; the third slice grouping of the second data
partition (e.g., slice group 2_3) is sent to the fourth DST
execution unit; the fourth slice grouping of the second data
partition (e.g., slice group 2_4, which includes first error coding
information) is sent to the fifth DST execution unit; and the fifth
slice grouping of the second data partition (e.g., slice group 2_5,
which includes second error coding information) is sent to the
first DST execution unit.
The pattern of sending the slice groupings to the set of DST
execution units may vary in a predicted pattern, a random pattern,
and/or a combination thereof from data partition to data partition.
In addition, from data partition to data partition, the set of DST
execution units may change. For example, for the first data
partition, DST execution units 1-5 may be used; for the second data
partition, DST execution units 6-10 may be used; for the third data
partition, DST execution units 3-7 may be used; etc. As is also
shown, the task is divided into partial tasks that are sent to the
DST execution units in conjunction with the slice groupings of the
data partitions.
FIG. 11 is a schematic block diagram of an embodiment of a DST
(distributed storage and/or task) execution unit that includes an
interface 169, a controller 86, memory 88, one or more DT
(distributed task) execution modules 90, and a DST client module
34. The memory 88 is of sufficient size to store a significant
number of encoded data slices (e.g., thousands of slices to
hundreds-of-millions of slices) and may include one or more hard
drives and/or one or more solid-state memory devices (e.g., flash
memory, DRAM, etc.).
In an example of storing a slice group, the DST execution module
receives a slice grouping 96 (e.g., slice group #1) via interface
169. The slice grouping 96 includes, per partition, encoded data
slices of contiguous data or encoded data slices of error coding
(EC) data. For slice group #1, the DST execution module receives
encoded data slices of contiguous data for partitions #1 and #x
(and potentially others between 3 and x) and receives encoded data
slices of EC data for partitions #2 and #3 (and potentially others
between 3 and x). Examples of encoded data slices of contiguous
data and encoded data slices of error coding (EC) data are
discussed with reference to FIG. 9. The memory 88 stores the
encoded data slices of slice groupings 96 in accordance with memory
control information 174 it receives from the controller 86.
The controller 86 (e.g., a processing module, a CPU, etc.)
generates the memory control information 174 based on a partial
task(s) 98 and distributed computing information (e.g., user
information (e.g., user ID, distributed computing permissions, data
access permission, etc.), vault information (e.g., virtual memory
assigned to user, user group, temporary storage for task
processing, etc.), task validation information, etc.). For example,
the controller 86 interprets the partial task(s) 98 in light of the
distributed computing information to determine whether a requestor
is authorized to perform the task 98, is authorized to access the
data, and/or is authorized to perform the task on this particular
data. When the requestor is authorized, the controller 86
determines, based on the task 98 and/or another input, whether the
encoded data slices of the slice grouping 96 are to be temporarily
stored or permanently stored. Based on the foregoing, the
controller 86 generates the memory control information 174 to write
the encoded data slices of the slice grouping 96 into the memory 88
and to indicate whether the slice grouping 96 is permanently stored
or temporarily stored.
With the slice grouping 96 stored in the memory 88, the controller
86 facilitates execution of the partial task(s) 98. In an example,
the controller 86 interprets the partial task 98 in light of the
capabilities of the DT execution module(s) 90. The capabilities
include one or more of MIPS capabilities, processing resources
(e.g., quantity and capability of microprocessors, CPUs, digital
signal processors, co-processor, microcontrollers, arithmetic logic
circuitry, and/or any other analog and/or digital processing
circuitry), availability of the processing resources, etc. If the
controller 86 determines that the DT execution module(s) 90 have
sufficient capabilities, it generates task control information
176.
The task control information 176 may be a generic instruction
(e.g., perform the task on the stored slice grouping) or a series
of operational codes. In the former instance, the DT execution
module 90 includes a co-processor function specifically configured
(fixed or programmed) to perform the desired task 98. In the latter
instance, the DT execution module 90 includes a general processor
topology where the controller stores an algorithm corresponding to
the particular task 98. In this instance, the controller 86
provides the operational codes (e.g., assembly language, source
code of a programming language, object code, etc.) of the algorithm
to the DT execution module 90 for execution.
Depending on the nature of the task 98, the DT execution module 90
may generate intermediate partial results 102 that are stored in
the memory 88 or in a cache memory (not shown) within the DT
execution module 90. In either case, when the DT execution module
90 completes execution of the partial task 98, it outputs one or
more partial results 102. The partial results 102 may also be
stored in memory 88.
If, when the controller 86 is interpreting whether capabilities of
the DT execution module(s) 90 can support the partial task 98, the
controller 86 determines that the DT execution module(s) 90 cannot
adequately support the task 98 (e.g., does not have the right
resources, does not have sufficient available resources, available
resources would be too slow, etc.), it then determines whether the
partial task 98 should be fully offloaded or partially
offloaded.
If the controller 86 determines that the partial task 98 should be
fully offloaded, it generates DST control information 178 and
provides it to the DST client module 34. The DST control
information 178 includes the partial task 98, memory storage
information regarding the slice grouping 96, and distribution
instructions. The distribution instructions instruct the DST client
module 34 to divide the partial task 98 into sub-partial tasks 172,
to divide the slice grouping 96 into sub-slice groupings 170, and
identify other DST execution units. The DST client module 34
functions in a similar manner as the DST client module 34 of FIGS.
3-10 to produce the sub-partial tasks 172 and the sub-slice
groupings 170 in accordance with the distribution instructions.
The DST client module 34 receives DST feedback 168 (e.g.,
sub-partial results), via the interface 169, from the DST execution
units to which the task was offloaded. The DST client module 34
provides the sub-partial results to the DST execution unit, which
processes the sub-partial results to produce the partial result(s)
102.
If the controller 86 determines that the partial task 98 should be
partially offloaded, it determines what portion of the task 98
and/or slice grouping 96 should be processed locally and what
should be offloaded. For the portion that is being locally
processed, the controller 86 generates task control information 176
as previously discussed. For the portion that is being offloaded,
the controller 86 generates DST control information 178 as
previously discussed.
When the DST client module 34 receives DST feedback 168 (e.g.,
sub-partial results) from the DST executions units to which a
portion of the task was offloaded, it provides the sub-partial
results to the DT execution module 90. The DT execution module 90
processes the sub-partial results with the sub-partial results it
created to produce the partial result(s) 102.
The memory 88 may be further utilized to retrieve one or more of
stored slices 100, stored results 104, partial results 102 when the
DT execution module 90 stores partial results 102 and/or results
104 in the memory 88. For example, when the partial task 98
includes a retrieval request, the controller 86 outputs the memory
control 174 to the memory 88 to facilitate retrieval of slices 100
and/or results 104.
FIG. 12 is a schematic block diagram of an example of operation of
a distributed storage and task (DST) execution unit storing encoded
data slices and executing a task thereon. To store the encoded data
slices of a partition 1 of slice grouping 1, a controller 86
generates write commands as memory control information 174 such
that the encoded slices are stored in desired locations (e.g.,
permanent or temporary) within memory 88.
Once the encoded slices are stored, the controller 86 provides task
control information 176 to a distributed task (DT) execution module
90. As a first step of executing the task in accordance with the
task control information 176, the DT execution module 90 retrieves
the encoded slices from memory 88. The DT execution module 90 then
reconstructs contiguous data blocks of a data partition. As shown
for this example, reconstructed contiguous data blocks of data
partition 1 include data blocks 1-15 (e.g., d1-d15).
With the contiguous data blocks reconstructed, the DT execution
module 90 performs the task on the reconstructed contiguous data
blocks. For example, the task may be to search the reconstructed
contiguous data blocks for a particular word or phrase, identify
where in the reconstructed contiguous data blocks the particular
word or phrase occurred, and/or count the occurrences of the
particular word or phrase on the reconstructed contiguous data
blocks. The DST execution unit continues in a similar manner for
the encoded data slices of other partitions in slice grouping 1.
Note that with using the unity matrix error encoding scheme
previously discussed, if the encoded data slices of contiguous data
are uncorrupted, the decoding of them is a relatively
straightforward process of extracting the data.
If, however, an encoded data slice of contiguous data is corrupted
(or missing), it can be rebuilt by accessing other DST execution
units that are storing the other encoded data slices of the set of
encoded data slices of the corrupted encoded data slice. In this
instance, the DST execution unit having the corrupted encoded data
slices retrieves at least three encoded data slices (of contiguous
data and of error coding data) in the set from the other DST
execution units (recall for this example, the pillar width is 5 and
the decode threshold is 3). The DST execution unit decodes the
retrieved data slices using the DS error encoding parameters to
recapture the corresponding data segment. The DST execution unit
then re-encodes the data segment using the DS error encoding
parameters to rebuild the corrupted encoded data slice. Once the
encoded data slice is rebuilt, the DST execution unit functions as
previously described.
FIG. 13 is a schematic block diagram of an embodiment of an inbound
distributed storage and/or task (DST) processing section 82 of a
DST client module coupled to DST execution units of a distributed
storage and task network (DSTN) module via a network 24. The
inbound DST processing section 82 includes a de-grouping module
180, a DS (dispersed storage) error decoding module 182, a data
de-partitioning module 184, a control module 186, and a distributed
task control module 188. Note that the control module 186 and/or
the distributed task control module 188 may be separate modules
from corresponding ones of outbound DST processing section or may
be the same modules.
In an example of operation, the DST execution units have completed
execution of corresponding partial tasks on the corresponding slice
groupings to produce partial results 102. The inbound DST
processing section 82 receives the partial results 102 via the
distributed task control module 188. The inbound DST processing
section 82 then processes the partial results 102 to produce a
final result, or results 104. For example, if the task was to find
a specific word or phrase within data, the partial results 102
indicate where in each of the prescribed portions of the data the
corresponding DST execution units found the specific word or
phrase. The distributed task control module 188 combines the
individual partial results 102 for the corresponding portions of
the data into a final result 104 for the data as a whole.
In another example of operation, the inbound DST processing section
82 is retrieving stored data from the DST execution units (i.e.,
the DSTN module). In this example, the DST execution units output
encoded data slices 100 corresponding to the data retrieval
requests. The de-grouping module 180 receives retrieved slices 100
and de-groups them to produce encoded data slices per data
partition 122. The DS error decoding module 182 decodes, in
accordance with DS error encoding parameters, the encoded data
slices per data partition 122 to produce data partitions 120.
The data de-partitioning module 184 combines the data partitions
120 into the data 92. The control module 186 controls the
conversion of retrieved slices 100 into the data 92 using control
signals 190 to each of the modules. For instance, the control
module 186 provides de-grouping information to the de-grouping
module 180, provides the DS error encoding parameters to the DS
error decoding module 182, and provides de-partitioning information
to the data de-partitioning module 184.
FIG. 14 is a logic diagram of an example of a method that is
executable by distributed storage and task (DST) client module
regarding inbound DST processing. The method begins at step 194
where the DST client module receives partial results. The method
continues at step 196 where the DST client module retrieves the
task corresponding to the partial results. For example, the partial
results include header information that identifies the requesting
entity, which correlates to the requested task.
The method continues at step 198 where the DST client module
determines result processing information based on the task. For
example, if the task were to identify a particular word or phrase
within the data, the result processing information would indicate
to aggregate the partial results for the corresponding portions of
the data to produce the final result. As another example, if the
task were to count the occurrences of a particular word or phrase
within the data, results of processing the information would
indicate to add the partial results to produce the final results.
The method continues at step 200 where the DST client module
processes the partial results in accordance with the result
processing information to produce the final result or results.
FIG. 15 is a diagram of an example of de-grouping selection
processing of an inbound distributed storage and task (DST)
processing section of a DST client module. In general, this is an
inverse process of the grouping module of the outbound DST
processing section of FIG. 9. Accordingly, for each data partition
(e.g., partition #1), the de-grouping module retrieves the
corresponding slice grouping from the DST execution units (EU)
(e.g., DST 1-5).
As shown, DST execution unit #1 provides a first slice grouping,
which includes the first encoded slices of each of the sets of
encoded slices (e.g., encoded data slices of contiguous data of
data blocks 1-15); DST execution unit #2 provides a second slice
grouping, which includes the second encoded slices of each of the
sets of encoded slices (e.g., encoded data slices of contiguous
data of data blocks 16-30); DST execution unit #3 provides a third
slice grouping, which includes the third encoded slices of each of
the sets of encoded slices (e.g., encoded data slices of contiguous
data of data blocks 31-45); DST execution unit #4 provides a fourth
slice grouping, which includes the fourth encoded slices of each of
the sets of encoded slices (e.g., first encoded data slices of
error coding (EC) data); and DST execution unit #5 provides a fifth
slice grouping, which includes the fifth encoded slices of each of
the sets of encoded slices (e.g., first encoded data slices of
error coding (EC) data).
The de-grouping module de-groups the slice groupings (e.g.,
received slices 100) using a de-grouping selector 180 controlled by
a control signal 190 as shown in the example to produce a plurality
of sets of encoded data slices (e.g., retrieved slices for a
partition into sets of slices 122). Each set corresponding to a
data segment of the data partition.
FIG. 16 is a schematic block diagram of an embodiment of a
dispersed storage (DS) error decoding module 182 of an inbound
distributed storage and task (DST) processing section. The DS error
decoding module 182 includes an inverse per slice security
processing module 202, a de-slicing module 204, an error decoding
module 206, an inverse segment security module 208, a de-segmenting
processing module 210, and a control module 186.
In an example of operation, the inverse per slice security
processing module 202, when enabled by the control module 186,
unsecures each encoded data slice 122 based on slice de-security
information received as control information 190 (e.g., the
compliment of the slice security information discussed with
reference to FIG. 6) received from the control module 186. The
slice security information includes data decompression, decryption,
de-watermarking, integrity check (e.g., CRC verification, etc.),
and/or any other type of digital security. For example, when the
inverse per slice security processing module 202 is enabled, it
verifies integrity information (e.g., a CRC value) of each encoded
data slice 122, it decrypts each verified encoded data slice, and
decompresses each decrypted encoded data slice to produce slice
encoded data 158. When the inverse per slice security processing
module 202 is not enabled, it passes the encoded data slices 122 as
the sliced encoded data 158 or is bypassed such that the retrieved
encoded data slices 122 are provided as the sliced encoded data
158.
The de-slicing module 204 de-slices the sliced encoded data 158
into encoded data segments 156 in accordance with a pillar width of
the error correction encoding parameters received as control
information 190 from the control module 186. For example, if the
pillar width is five, the de-slicing module 204 de-slices a set of
five encoded data slices into an encoded data segment 156. The
error decoding module 206 decodes the encoded data segments 156 in
accordance with error correction decoding parameters received as
control information 190 from the control module 186 to produce
secure data segments 154. The error correction decoding parameters
include identifying an error correction encoding scheme (e.g.,
forward error correction algorithm, a Reed-Solomon based algorithm,
an information dispersal algorithm, etc.), a pillar width, a decode
threshold, a read threshold, a write threshold, etc. For example,
the error correction decoding parameters identify a specific error
correction encoding scheme, specify a pillar width of five, and
specify a decode threshold of three.
The inverse segment security processing module 208, when enabled by
the control module 186, unsecures the secured data segments 154
based on segment security information received as control
information 190 from the control module 186. The segment security
information includes data decompression, decryption,
de-watermarking, integrity check (e.g., CRC, etc.) verification,
and/or any other type of digital security. For example, when the
inverse segment security processing module 208 is enabled, it
verifies integrity information (e.g., a CRC value) of each secure
data segment 154, it decrypts each verified secured data segment,
and decompresses each decrypted secure data segment to produce a
data segment 152. When the inverse segment security processing
module 208 is not enabled, it passes the decoded data segment 154
as the data segment 152 or is bypassed.
The de-segment processing module 210 receives the data segments 152
and receives de-segmenting information as control information 190
from the control module 186. The de-segmenting information
indicates how the de-segment processing module 210 is to de-segment
the data segments 152 into a data partition 120. For example, the
de-segmenting information indicates how the rows and columns of
data segments are to be rearranged to yield the data partition
120.
FIG. 17 is a diagram of an example of de-slicing and error decoding
processing of a dispersed error decoding module. A de-slicing
module 204 receives at least a decode threshold number of encoded
data slices 158 for each data segment in accordance with control
information 190 and provides encoded data 156. In this example, a
decode threshold is three. As such, each set of encoded data slices
158 is shown to have three encoded data slices per data segment.
The de-slicing module 204 may receive three encoded data slices per
data segment because an associated distributed storage and task
(DST) client module requested retrieving only three encoded data
slices per segment or selected three of the retrieved encoded data
slices per data segment. As shown, which is based on the unity
matrix encoding previously discussed with reference to FIG. 8, an
encoded data slice may be a data-based encoded data slice (e.g.,
DS1_d1&d2) or an error code based encoded data slice (e.g.,
ES3_1).
An error decoding module 206 decodes the encoded data 156 of each
data segment in accordance with the error correction decoding
parameters of control information 190 to produce secured segments
154. In this example, data segment 1 includes 3 rows with each row
being treated as one word for encoding. As such, data segment 1
includes three words: word 1 including data blocks d1 and d2, word
2 including data blocks d16 and d17, and word 3 including data
blocks d31 and d32. Each of data segments 2-7 includes three words
where each word includes two data blocks. Data segment 8 includes
three words where each word includes a single data block (e.g.,
d15, d30, and d45).
FIG. 18 is a diagram of an example of de-segment processing of an
inbound distributed storage and task (DST) processing. In this
example, a de-segment processing module 210 receives data segments
152 (e.g., 1-8) and rearranges the data blocks of the data segments
into rows and columns in accordance with de-segmenting information
of control information 190 to produce a data partition 120. Note
that the number of rows is based on the decode threshold (e.g., 3
in this specific example) and the number of columns is based on the
number and size of the data blocks.
The de-segmenting module 210 converts the rows and columns of data
blocks into the data partition 120. Note that each data block may
be of the same size as other data blocks or of a different size. In
addition, the size of each data block may be a few bytes to
megabytes of data.
FIG. 19 is a diagram of an example of converting slice groups into
data 92 within an inbound distributed storage and task (DST)
processing section. As shown, the data 92 is reconstructed from a
plurality of data partitions (1-x, where x is an integer greater
than 4). Each data partition (or chunk set of data) is decoded and
re-grouped using a de-grouping and decoding function 212 and a
de-partition function 214 from slice groupings as previously
discussed. For a given data partition, the slice groupings (e.g.,
at least a decode threshold per data segment of encoded data
slices) are received from DST execution units. From data partition
to data partition, the ordering of the slice groupings received
from the DST execution units may vary as discussed with reference
to FIG. 10.
FIG. 20 is a diagram of an example of a distributed storage and/or
retrieval within the distributed computing system. The distributed
computing system includes a plurality of distributed storage and/or
task (DST) processing client modules 34 (one shown) coupled to a
distributed storage and/or task processing network (DSTN) module,
or multiple DSTN modules, via a network 24. The DST client module
34 includes an outbound DST processing section 80 and an inbound
DST processing section 82. The DSTN module includes a plurality of
DST execution units. Each DST execution unit includes a controller
86, memory 88, one or more distributed task (DT) execution modules
90, and a DST client module 34.
In an example of data storage, the DST client module 34 has data 92
that it desires to store in the DSTN module. The data 92 may be a
file (e.g., video, audio, text, graphics, etc.), a data object, a
data block, an update to a file, an update to a data block, etc. In
this instance, the outbound DST processing module 80 converts the
data 92 into encoded data slices 216 as will be further described
with reference to FIGS. 21-23. The outbound DST processing module
80 sends, via the network 24, to the DST execution units for
storage as further described with reference to FIG. 24.
In an example of data retrieval, the DST client module 34 issues a
retrieve request to the DST execution units for the desired data
92. The retrieve request may address each DST executions units
storing encoded data slices of the desired data, address a decode
threshold number of DST execution units, address a read threshold
number of DST execution units, or address some other number of DST
execution units. In response to the request, each addressed DST
execution unit retrieves its encoded data slices 100 of the desired
data and sends them to the inbound DST processing section 82, via
the network 24.
When, for each data segment, the inbound DST processing section 82
receives at least a decode threshold number of encoded data slices
100, it converts the encoded data slices 100 into a data segment.
The inbound DST processing section 82 aggregates the data segments
to produce the retrieved data 92.
FIG. 21 is a schematic block diagram of an embodiment of an
outbound distributed storage and/or task (DST) processing section
80 of a DST client module coupled to a distributed storage and task
network (DSTN) module (e.g., a plurality of DST execution units)
via a network 24. The outbound DST processing section 80 includes a
data partitioning module 110, a dispersed storage (DS) error
encoding module 112, a grouping selector module 114, a control
module 116, and a distributed task control module 118.
In an example of operation, the data partitioning module 110 is
by-passed such that data 92 is provided directly to the DS error
encoding module 112. The control module 116 coordinates the
by-passing of the data partitioning module 110 by outputting a
bypass 220 message to the data partitioning module 110.
The DS error encoding module 112 receives the data 92 in a serial
manner, a parallel manner, and/or a combination thereof. The DS
error encoding module 112 DS error encodes the data in accordance
with control information 160 from the control module 116 to produce
encoded data slices 218. The DS error encoding includes segmenting
the data 92 into data segments, segment security processing (e.g.,
encryption, compression, watermarking, integrity check (e.g., CRC,
etc.)), error encoding, slicing, and/or per slice security
processing (e.g., encryption, compression, watermarking, integrity
check (e.g., CRC, etc.)). The control information 160 indicates
which steps of the DS error encoding are active for the data 92
and, for active steps, indicates the parameters for the step. For
example, the control information 160 indicates that the error
encoding is active and includes error encoding parameters (e.g.,
pillar width, decode threshold, write threshold, read threshold,
type of error encoding, etc.).
The grouping selector module 114 groups the encoded slices 218 of
the data segments into pillars of slices 216. The number of pillars
corresponds to the pillar width of the DS error encoding
parameters. In this example, the distributed task control module
118 facilitates the storage request.
FIG. 22 is a schematic block diagram of an example of a dispersed
storage (DS) error encoding module 112 for the example of FIG. 21.
The DS error encoding module 112 includes a segment processing
module 142, a segment security processing module 144, an error
encoding module 146, a slicing module 148, and a per slice security
processing module 150. Each of these modules is coupled to a
control module 116 to receive control information 160
therefrom.
In an example of operation, the segment processing module 142
receives data 92 and receives segmenting information as control
information 160 from the control module 116. The segmenting
information indicates how the segment processing module is to
segment the data. For example, the segmenting information indicates
the size of each data segment. The segment processing module 142
segments the data 92 into data segments 152 in accordance with the
segmenting information.
The segment security processing module 144, when enabled by the
control module 116, secures the data segments 152 based on segment
security information received as control information 160 from the
control module 116. The segment security information includes data
compression, encryption, watermarking, integrity check (e.g., CRC,
etc.), and/or any other type of digital security. For example, when
the segment security processing module 144 is enabled, it
compresses a data segment 152, encrypts the compressed data
segment, and generates a CRC value for the encrypted data segment
to produce a secure data segment. When the segment security
processing module 144 is not enabled, it passes the data segments
152 to the error encoding module 146 or is bypassed such that the
data segments 152 are provided to the error encoding module
146.
The error encoding module 146 encodes the secure data segments in
accordance with error correction encoding parameters received as
control information 160 from the control module 116. The error
correction encoding parameters include identifying an error
correction encoding scheme (e.g., forward error correction
algorithm, a Reed-Solomon based algorithm, an information dispersal
algorithm, etc.), a pillar width, a decode threshold, a read
threshold, a write threshold, etc. For example, the error
correction encoding parameters identify a specific error correction
encoding scheme, specifies a pillar width of five, and specifies a
decode threshold of three. From these parameters, the error
encoding module 146 encodes a data segment to produce an encoded
data segment.
The slicing module 148 slices the encoded data segment in
accordance with a pillar width of the error correction encoding
parameters. For example, if the pillar width is five, the slicing
module slices an encoded data segment into a set of five encoded
data slices. As such, for a plurality of data segments, the slicing
module 148 outputs a plurality of sets of encoded data slices as
shown within encoding and slicing function 222 as described.
The per slice security processing module 150, when enabled by the
control module 116, secures each encoded data slice based on slice
security information received as control information 160 from the
control module 116. The slice security information includes data
compression, encryption, watermarking, integrity check (e.g., CRC,
etc.), and/or any other type of digital security. For example, when
the per slice security processing module 150 is enabled, it may
compress an encoded data slice, encrypt the compressed encoded data
slice, and generate a CRC value for the encrypted encoded data
slice to produce a secure encoded data slice tweaking. When the per
slice security processing module 150 is not enabled, it passes the
encoded data slices or is bypassed such that the encoded data
slices 218 are the output of the DS error encoding module 112.
FIG. 23 is a diagram of an example of converting data 92 into
pillar slice groups utilizing encoding, slicing and pillar grouping
function 224 for storage in memory of a distributed storage and
task network (DSTN) module. As previously discussed the data 92 is
encoded and sliced into a plurality of sets of encoded data slices;
one set per data segment. The grouping selector module organizes
the sets of encoded data slices into pillars of data slices. In
this example, the DS error encoding parameters include a pillar
width of 5 and a decode threshold of 3. As such, for each data
segment, 5 encoded data slices are created.
The grouping selector module takes the first encoded data slice of
each of the sets and forms a first pillar, which may be sent to the
first DST execution unit. Similarly, the grouping selector module
creates the second pillar from the second slices of the sets; the
third pillar from the third slices of the sets; the fourth pillar
from the fourth slices of the sets; and the fifth pillar from the
fifth slices of the set.
FIG. 24 is a schematic block diagram of an embodiment of a
distributed storage and/or task (DST) execution unit that includes
an interface 169, a controller 86, memory 88, one or more
distributed task (DT) execution modules 90, and a DST client module
34. A computing core 26 may be utilized to implement the one or
more DT execution modules 90 and the DST client module 34. The
memory 88 is of sufficient size to store a significant number of
encoded data slices (e.g., thousands of slices to
hundreds-of-millions of slices) and may include one or more hard
drives and/or one or more solid-state memory devices (e.g., flash
memory, DRAM, etc.).
In an example of storing a pillar of slices 216, the DST execution
unit receives, via interface 169, a pillar of slices 216 (e.g.,
pillar #1 slices). The memory 88 stores the encoded data slices 216
of the pillar of slices in accordance with memory control
information 174 it receives from the controller 86. The controller
86 (e.g., a processing module, a CPU, etc.) generates the memory
control information 174 based on distributed storage information
(e.g., user information (e.g., user ID, distributed storage
permissions, data access permission, etc.), vault information
(e.g., virtual memory assigned to user, user group, etc.), etc.).
Similarly, when retrieving slices, the DST execution unit receives,
via interface 169, a slice retrieval request. The memory 88
retrieves the slice in accordance with memory control information
174 it receives from the controller 86. The memory 88 outputs the
slice 100, via the interface 169, to a requesting entity.
FIG. 25 is a schematic block diagram of an example of operation of
an inbound distributed storage and/or task (DST) processing section
82 for retrieving dispersed error encoded data 92. The inbound DST
processing section 82 includes a de-grouping module 180, a
dispersed storage (DS) error decoding module 182, a data
de-partitioning module 184, a control module 186, and a distributed
task control module 188. Note that the control module 186 and/or
the distributed task control module 188 may be separate modules
from corresponding ones of an outbound DST processing section or
may be the same modules.
In an example of operation, the inbound DST processing section 82
is retrieving stored data 92 from the DST execution units (i.e.,
the DSTN module). In this example, the DST execution units output
encoded data slices corresponding to data retrieval requests from
the distributed task control module 188. The de-grouping module 180
receives pillars of slices 100 and de-groups them in accordance
with control information 190 from the control module 186 to produce
sets of encoded data slices 218. The DS error decoding module 182
decodes, in accordance with the DS error encoding parameters
received as control information 190 from the control module 186,
each set of encoded data slices 218 to produce data segments, which
are aggregated into retrieved data 92. The data de-partitioning
module 184 is by-passed in this operational mode via a bypass
signal 226 of control information 190 from the control module
186.
FIG. 26 is a schematic block diagram of an embodiment of a
dispersed storage (DS) error decoding module 182 of an inbound
distributed storage and task (DST) processing section. The DS error
decoding module 182 includes an inverse per slice security
processing module 202, a de-slicing module 204, an error decoding
module 206, an inverse segment security module 208, and a
de-segmenting processing module 210. The dispersed error decoding
module 182 is operable to de-slice and decode encoded slices per
data segment 218 utilizing a de-slicing and decoding function 228
to produce a plurality of data segments that are de-segmented
utilizing a de-segment function 230 to recover data 92.
In an example of operation, the inverse per slice security
processing module 202, when enabled by the control module 186 via
control information 190, unsecures each encoded data slice 218
based on slice de-security information (e.g., the compliment of the
slice security information discussed with reference to FIG. 6)
received as control information 190 from the control module 186.
The slice de-security information includes data decompression,
decryption, de-watermarking, integrity check (e.g., CRC
verification, etc.), and/or any other type of digital security. For
example, when the inverse per slice security processing module 202
is enabled, it verifies integrity information (e.g., a CRC value)
of each encoded data slice 218, it decrypts each verified encoded
data slice, and decompresses each decrypted encoded data slice to
produce slice encoded data. When the inverse per slice security
processing module 202 is not enabled, it passes the encoded data
slices 218 as the sliced encoded data or is bypassed such that the
retrieved encoded data slices 218 are provided as the sliced
encoded data.
The de-slicing module 204 de-slices the sliced encoded data into
encoded data segments in accordance with a pillar width of the
error correction encoding parameters received as control
information 190 from a control module 186. For example, if the
pillar width is five, the de-slicing module de-slices a set of five
encoded data slices into an encoded data segment. Alternatively,
the encoded data segment may include just three encoded data slices
(e.g., when the decode threshold is 3).
The error decoding module 206 decodes the encoded data segments in
accordance with error correction decoding parameters received as
control information 190 from the control module 186 to produce
secure data segments. The error correction decoding parameters
include identifying an error correction encoding scheme (e.g.,
forward error correction algorithm, a Reed-Solomon based algorithm,
an information dispersal algorithm, etc.), a pillar width, a decode
threshold, a read threshold, a write threshold, etc. For example,
the error correction decoding parameters identify a specific error
correction encoding scheme, specify a pillar width of five, and
specify a decode threshold of three.
The inverse segment security processing module 208, when enabled by
the control module 186, unsecures the secured data segments based
on segment security information received as control information 190
from the control module 186. The segment security information
includes data decompression, decryption, de-watermarking, integrity
check (e.g., CRC, etc.) verification, and/or any other type of
digital security. For example, when the inverse segment security
processing module is enabled, it verifies integrity information
(e.g., a CRC value) of each secure data segment, it decrypts each
verified secured data segment, and decompresses each decrypted
secure data segment to produce a data segment 152. When the inverse
segment security processing module 208 is not enabled, it passes
the decoded data segment 152 as the data segment or is bypassed.
The de-segmenting processing module 210 aggregates the data
segments 152 into the data 92 in accordance with control
information 190 from the control module 186.
FIG. 27 is a schematic block diagram of an example of a distributed
storage and task processing network (DSTN) module that includes a
plurality of distributed storage and task (DST) execution units (#1
through #n, where, for example, n is an integer greater than or
equal to three). Each of the DST execution units includes a DST
client module 34, a controller 86, one or more DT (distributed
task) execution modules 90, and memory 88.
In this example, the DSTN module stores, in the memory of the DST
execution units, a plurality of DS (dispersed storage) encoded data
(e.g., 1 through n, where n is an integer greater than or equal to
two) and stores a plurality of DS encoded task codes (e.g., 1
through k, where k is an integer greater than or equal to two). The
DS encoded data may be encoded in accordance with one or more
examples described with reference to FIGS. 3-19 (e.g., organized in
slice groupings) or encoded in accordance with one or more examples
described with reference to FIGS. 20-26 (e.g., organized in pillar
groups). The data that is encoded into the DS encoded data may be
of any size and/or of any content. For example, the data may be one
or more digital books, a copy of a company's emails, a large-scale
Internet search, a video security file, one or more entertainment
video files (e.g., television programs, movies, etc.), data files,
and/or any other large amount of data (e.g., greater than a few
Terabytes).
The tasks that are encoded into the DS encoded task code may be a
simple function (e.g., a mathematical function, a logic function,
an identify function, a find function, a search engine function, a
replace function, etc.), a complex function (e.g., compression,
human and/or computer language translation, text-to-voice
conversion, voice-to-text conversion, etc.), multiple simple and/or
complex functions, one or more algorithms, one or more
applications, etc. The tasks may be encoded into the DS encoded
task code in accordance with one or more examples described with
reference to FIGS. 3-19 (e.g., organized in slice groupings) or
encoded in accordance with one or more examples described with
reference to FIGS. 20-26 (e.g., organized in pillar groups).
In an example of operation, a DST client module of a user device or
of a DST processing unit issues a DST request to the DSTN module.
The DST request may include a request to retrieve stored data, or a
portion thereof, may include a request to store data that is
included with the DST request, may include a request to perform one
or more tasks on stored data, may include a request to perform one
or more tasks on data included with the DST request, etc. In the
cases where the DST request includes a request to store data or to
retrieve data, the client module and/or the DSTN module processes
the request as previously discussed with reference to one or more
of FIGS. 3-19 (e.g., slice groupings) and/or 20-26 (e.g., pillar
groupings). In the case where the DST request includes a request to
perform one or more tasks on data included with the DST request,
the DST client module and/or the DSTN module process the DST
request as previously discussed with reference to one or more of
FIGS. 3-19.
In the case where the DST request includes a request to perform one
or more tasks on stored data, the DST client module and/or the DSTN
module processes the DST request as will be described with
reference to one or more of FIGS. 28-39. In general, the DST client
module identifies data and one or more tasks for the DSTN module to
execute upon the identified data. The DST request may be for a
one-time execution of the task or for an on-going execution of the
task. As an example of the latter, as a company generates daily
emails, the DST request may be to daily search new emails for
inappropriate content and, if found, record the content, the email
sender(s), the email recipient(s), email routing information,
notify human resources of the identified email, etc.
FIG. 28 is a schematic block diagram of an example of a distributed
computing system performing tasks on stored data. In this example,
two distributed storage and task (DST) client modules 1-2 are
shown: the first may be associated with a user device and the
second may be associated with a DST processing unit or a high
priority user device (e.g., high priority clearance user, system
administrator, etc.). Each DST client module includes a list of
stored data 234 and a list of tasks codes 236. The list of stored
data 234 includes one or more entries of data identifying
information, where each entry identifies data stored in the DSTN
module 22. The data identifying information (e.g., data ID)
includes one or more of a data file name, a data file directory
listing, DSTN addressing information of the data, a data object
identifier, etc. The list of tasks 236 includes one or more entries
of task code identifying information, when each entry identifies
task codes stored in the DSTN module 22. The task code identifying
information (e.g., task ID) includes one or more of a task file
name, a task file directory listing, DSTN addressing information of
the task, another type of identifier to identify the task, etc.
As shown, the list of data 234 and the list of tasks 236 are each
smaller in number of entries for the first DST client module than
the corresponding lists of the second DST client module. This may
occur because the user device associated with the first DST client
module has fewer privileges in the distributed computing system
than the device associated with the second DST client module.
Alternatively, this may occur because the user device associated
with the first DST client module serves fewer users than the device
associated with the second DST client module and is restricted by
the distributed computing system accordingly. As yet another
alternative, this may occur through no restraints by the
distributed computing system, it just occurred because the operator
of the user device associated with the first DST client module has
selected fewer data and/or fewer tasks than the operator of the
device associated with the second DST client module.
In an example of operation, the first DST client module selects one
or more data entries 238 and one or more tasks 240 from its
respective lists (e.g., selected data ID and selected task ID). The
first DST client module sends its selections to a task distribution
module 232. The task distribution module 232 may be within a
stand-alone device of the distributed computing system, may be
within the user device that contains the first DST client module,
or may be within the DSTN module 22.
Regardless of the task distribution module's location, it generates
DST allocation information 242 from the selected task ID 240 and
the selected data ID 238. The DST allocation information 242
includes data partitioning information, task execution information,
and/or intermediate result information. The task distribution
module 232 sends the DST allocation information 242 to the DSTN
module 22. Note that one or more examples of the DST allocation
information will be discussed with reference to one or more of
FIGS. 29-39.
The DSTN module 22 interprets the DST allocation information 242 to
identify the stored DS encoded data (e.g., DS error encoded data 2)
and to identify the stored DS error encoded task code (e.g., DS
error encoded task code 1). In addition, the DSTN module 22
interprets the DST allocation information 242 to determine how the
data is to be partitioned and how the task is to be partitioned.
The DSTN module 22 also determines whether the selected DS error
encoded data 238 needs to be converted from pillar grouping to
slice grouping. If so, the DSTN module 22 converts the selected DS
error encoded data into slice groupings and stores the slice
grouping DS error encoded data by overwriting the pillar grouping
DS error encoded data or by storing it in a different location in
the memory of the DSTN module 22 (i.e., does not overwrite the
pillar grouping DS encoded data).
The DSTN module 22 partitions the data and the task as indicated in
the DST allocation information 242 and sends the portions to
selected DST execution units of the DSTN module 22. Each of the
selected DST execution units performs its partial task(s) on its
slice groupings to produce partial results. The DSTN module 22
collects the partial results from the selected DST execution units
and provides them, as result information 244, to the task
distribution module. The result information 244 may be the
collected partial results, one or more final results as produced by
the DSTN module 22 from processing the partial results in
accordance with the DST allocation information 242, or one or more
intermediate results as produced by the DSTN module 22 from
processing the partial results in accordance with the DST
allocation information 242.
The task distribution module 232 receives the result information
244 and provides one or more final results 104 therefrom to the
first DST client module. The final result(s) 104 may be result
information 244 or a result(s) of the task distribution module's
processing of the result information 244.
In concurrence with processing the selected task of the first DST
client module, the distributed computing system may process the
selected task(s) of the second DST client module on the selected
data(s) of the second DST client module. Alternatively, the
distributed computing system may process the second DST client
module's request subsequent to, or preceding, that of the first DST
client module. Regardless of the ordering and/or parallel
processing of the DST client module requests, the second DST client
module provides its selected data 238 and selected task 240 to a
task distribution module 232. If the task distribution module 232
is a separate device of the distributed computing system or within
the DSTN module, the task distribution modules 232 coupled to the
first and second DST client modules may be the same module. The
task distribution module 232 processes the request of the second
DST client module in a similar manner as it processed the request
of the first DST client module.
FIG. 29 is a schematic block diagram of an embodiment of a task
distribution module 232 facilitating the example of FIG. 28. The
task distribution module 232 includes a plurality of tables it uses
to generate distributed storage and task (DST) allocation
information 242 for selected data and selected tasks received from
a DST client module. The tables include data storage information
248, task storage information 250, distributed task (DT) execution
module information 252, and task .revreaction. sub-task mapping
information 246.
The data storage information table 248 includes a data
identification (ID) field 260, a data size field 262, an addressing
information field 264, distributed storage (DS) information 266,
and may further include other information regarding the data, how
it is stored, and/or how it can be processed. For example, DS
encoded data #1 has a data ID of 1, a data size of AA (e.g., a byte
size of a few Terabytes or more), addressing information of
Addr_1_AA, and DS parameters of 3/5; SEG_1; and SLC_1. In this
example, the addressing information may be a virtual address
corresponding to the virtual address of the first storage word
(e.g., one or more bytes) of the data and information on how to
calculate the other addresses, may be a range of virtual addresses
for the storage words of the data, physical addresses of the first
storage word or the storage words of the data, may be a list of
slice names of the encoded data slices of the data, etc. The DS
parameters may include identity of an error encoding scheme, decode
threshold/pillar width (e.g., 3/5 for the first data entry),
segment security information (e.g., SEG_1), per slice security
information (e.g., SLC_1), and/or any other information regarding
how the data was encoded into data slices.
The task storage information table 250 includes a task
identification (ID) field 268, a task size field 270, an addressing
information field 272, distributed storage (DS) information 274,
and may further include other information regarding the task, how
it is stored, and/or how it can be used to process data. For
example, DS encoded task #2 has a task ID of 2, a task size of XY,
addressing information of Addr_2_XY, and DS parameters of 3/5;
SEG_2; and SLC_2. In this example, the addressing information may
be a virtual address corresponding to the virtual address of the
first storage word (e.g., one or more bytes) of the task and
information on how to calculate the other addresses, may be a range
of virtual addresses for the storage words of the task, physical
addresses of the first storage word or the storage words of the
task, may be a list of slices names of the encoded slices of the
task code, etc. The DS parameters may include identity of an error
encoding scheme, decode threshold/pillar width (e.g., 3/5 for the
first data entry), segment security information (e.g., SEG_2), per
slice security information (e.g., SLC_2), and/or any other
information regarding how the task was encoded into encoded task
slices. Note that the segment and/or the per-slice security
information include a type of encryption (if enabled), a type of
compression (if enabled), watermarking information (if enabled),
and/or an integrity check scheme (if enabled).
The task .revreaction. sub-task mapping information table 246
includes a task field 256 and a sub-task field 258. The task field
256 identifies a task stored in the memory of a distributed storage
and task network (DSTN) module and the corresponding sub-task
fields 258 indicates whether the task includes sub-tasks and, if
so, how many and if any of the sub-tasks are ordered. In this
example, the task .revreaction. sub-task mapping information table
246 includes an entry for each task stored in memory of the DSTN
module (e.g., task 1 through task k). In particular, this example
indicates that task 1 includes 7 sub-tasks; task 2 does not include
sub-tasks, and task k includes r number of sub-tasks (where r is an
integer greater than or equal to two).
The DT execution module table 252 includes a DST execution unit ID
field 276, a DT execution module ID field 278, and a DT execution
module capabilities field 280. The DST execution unit ID field 276
includes the identity of DST units in the DSTN module. The DT
execution module ID field 278 includes the identity of each DT
execution unit in each DST unit. For example, DST unit 1 includes
three DT executions modules (e.g., 1_1, 1_2, and 1_3). The DT
execution capabilities field 280 includes identity of the
capabilities of the corresponding DT execution unit. For example,
DT execution module 1_1 includes capabilities X, where X includes
one or more of MIPS capabilities, processing resources (e.g.,
quantity and capability of microprocessors, CPUs, digital signal
processors, co-processor, microcontrollers, arithmetic logic
circuitry, and/or any other analog and/or digital processing
circuitry), availability of the processing resources, memory
information (e.g., type, size, availability, etc.), and/or any
information germane to executing one or more tasks.
From these tables, the task distribution module 232 generates the
DST allocation information 242 to indicate where the data is
stored, how to partition the data, where the task is stored, how to
partition the task, which DT execution units should perform which
partial task on which data partitions, where and how intermediate
results are to be stored, etc. If multiple tasks are being
performed on the same data or different data, the task distribution
module factors such information into its generation of the DST
allocation information.
FIG. 30 is a diagram of a specific example of a distributed
computing system performing tasks on stored data as a task flow
318. In this example, selected data 92 is data 2 and selected tasks
are tasks 1, 2, and 3. Task 1 corresponds to analyzing translation
of data from one language to another (e.g., human language or
computer language); task 2 corresponds to finding specific words
and/or phrases in the data; and task 3 corresponds to finding
specific translated words and/or phrases in translated data.
In this example, task 1 includes 7 sub-tasks: task 1_1--identify
non-words (non-ordered); task 1_2--identify unique words
(non-ordered); task 1_3--translate (non-ordered); task
1_4--translate back (ordered after task 1_3); task 1_5--compare to
ID errors (ordered after task 1-4); task 1_6--determine non-word
translation errors (ordered after task 1_5 and 1_1); and task
1_7--determine correct translations (ordered after 1_5 and 1_2).
The sub-task further indicates whether they are an ordered task
(i.e., are dependent on the outcome of another task) or non-order
(i.e., are independent of the outcome of another task). Task 2 does
not include sub-tasks and task 3 includes two sub-tasks: task 3_1
translate; and task 3_2 find specific word or phrase in translated
data.
In general, the three tasks collectively are selected to analyze
data for translation accuracies, translation errors, translation
anomalies, occurrence of specific words or phrases in the data, and
occurrence of specific words or phrases on the translated data.
Graphically, the data 92 is translated 306 into translated data
282; is analyzed for specific words and/or phrases 300 to produce a
list of specific words and/or phrases 286; is analyzed for
non-words 302 (e.g., not in a reference dictionary) to produce a
list of non-words 290; and is analyzed for unique words 316
included in the data 92 (i.e., how many different words are
included in the data) to produce a list of unique words 298. Each
of these tasks is independent of each other and can therefore be
processed in parallel if desired.
The translated data 282 is analyzed (e.g., sub-task 3_2) for
specific translated words and/or phrases 304 to produce a list of
specific translated words and/or phrases 288. The translated data
282 is translated back 308 (e.g., sub-task 1_4) into the language
of the original data to produce re-translated data 284. These two
tasks are dependent on the translate task (e.g., task 1_3) and thus
must be ordered after the translation task, which may be in a
pipelined ordering or a serial ordering. The re-translated data 284
is then compared 310 with the original data 92 to find words and/or
phrases that did not translate (one way and/or the other) properly
to produce a list of incorrectly translated words 294. As such, the
comparing task (e.g., sub-task 1_5) 310 is ordered after the
translation 306 and re-translation tasks 308 (e.g., sub-tasks 1_3
and 1_4).
The list of words incorrectly translated 294 is compared 312 to the
list of non-words 290 to identify words that were not properly
translated because the words are non-words to produce a list of
errors due to non-words 292. In addition, the list of words
incorrectly translated 294 is compared 314 to the list of unique
words 298 to identify unique words that were properly translated to
produce a list of correctly translated words 296. The comparison
may also identify unique words that were not properly translated to
produce a list of unique words that were not properly translated.
Note that each list of words (e.g., specific words and/or phrases,
non-words, unique words, translated words and/or phrases, etc.,)
may include the word and/or phrase, how many times it is used,
where in the data it is used, and/or any other information
requested regarding a word and/or phrase.
FIG. 31 is a schematic block diagram of an example of a distributed
storage and task processing network (DSTN) module storing data and
task codes for the example of FIG. 30. As shown, DS encoded data 2
is stored as encoded data slices across the memory (e.g., stored in
memories 88) of DST execution units 1-5; the DS encoded task code 1
(of task 1) and DS encoded task 3 are stored as encoded task slices
across the memory of DST execution units 1-5; and DS encoded task
code 2 (of task 2) is stored as encoded task slices across the
memory of DST execution units 3-7. As indicated in the data storage
information table and the task storage information table of FIG.
29, the respective data/task has DS parameters of 3/5 for their
decode threshold/pillar width; hence spanning the memory of five
DST execution units.
FIG. 32 is a diagram of an example of distributed storage and task
(DST) allocation information 242 for the example of FIG. 30. The
DST allocation information 242 includes data partitioning
information 320, task execution information 322, and intermediate
result information 324. The data partitioning information 320
includes the data identifier (ID), the number of partitions to
split the data into, address information for each data partition,
and whether the DS encoded data has to be transformed from pillar
grouping to slice grouping. The task execution information 322
includes tabular information having a task identification field
326, a task ordering field 328, a data partition field ID 330, and
a set of DT execution modules 332 to use for the distributed task
processing per data partition. The intermediate result information
324 includes tabular information having a name ID field 334, an ID
of the DST execution unit assigned to process the corresponding
intermediate result 336, a scratch pad storage field 338, and an
intermediate result storage field 340.
Continuing with the example of FIG. 30, where tasks 1-3 are to be
distributedly performed on data 2, the data partitioning
information includes the ID of data 2. In addition, the task
distribution module determines whether the DS encoded data 2 is in
the proper format for distributed computing (e.g., was stored as
slice groupings). If not, the task distribution module indicates
that the DS encoded data 2 format needs to be changed from the
pillar grouping format to the slice grouping format, which will be
done by the DSTN module. In addition, the task distribution module
determines the number of partitions to divide the data into (e.g.,
2_1 through 2_z) and addressing information for each partition.
The task distribution module generates an entry in the task
execution information section for each sub-task to be performed.
For example, task 1_1 (e.g., identify non-words on the data) has no
task ordering (i.e., is independent of the results of other
sub-tasks), is to be performed on data partitions 2_1 through 2_z
by DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1. For instance,
DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 search for
non-words in data partitions 2_1 through 2_z to produce task 1_1
intermediate results (R1-1, which is a list of non-words). Task 1_2
(e.g., identify unique words) has similar task execution
information as task 1_1 to produce task 1_2 intermediate results
(R1-2, which is the list of unique words).
Task 1_3 (e.g., translate) includes task execution information as
being non-ordered (i.e., is independent), having DT execution
modules 1_1, 2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1
through 2_4 and having DT execution modules 1_2, 2_2, 3_2, 4_2, and
5_2 translate data partitions 2_5 through 2_z to produce task 1_3
intermediate results (R1-3, which is the translated data). In this
example, the data partitions are grouped, where different sets of
DT execution modules perform a distributed sub-task (or task) on
each data partition group, which allows for further parallel
processing.
Task 1_4 (e.g., translate back) is ordered after task 1_3 and is to
be executed on task 1_3's intermediate result (e.g., R1-3_1) (e.g.,
the translated data). DT execution modules 1_1, 2_1, 3_1, 4_1, and
5_1 are allocated to translate back task 1_3 intermediate result
partitions R1-3_1 through R1-3_4 and DT execution modules 1_2, 2_2,
6_1, 7_1, and 7_2 are allocated to translate back task 1_3
intermediate result partitions R1-3_5 through R1-3_z to produce
task 1-4 intermediate results (R1-4, which is the translated back
data).
Task 1_5 (e.g., compare data and translated data to identify
translation errors) is ordered after task 1_4 and is to be executed
on task 1_4's intermediate results (R4-1) and on the data. DT
execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 are allocated to
compare the data partitions (2_1 through 2_z) with partitions of
task 1-4 intermediate results partitions R1-4_1 through R1-4_z to
produce task 1_5 intermediate results (R1-5, which is the list
words translated incorrectly).
Task 1_6 (e.g., determine non-word translation errors) is ordered
after tasks 1_1 and 1_5 and is to be executed on tasks 1_1's and
1_5's intermediate results (R1-1 and R1-5). DT execution modules
1_1, 2_1, 3_1, 4_1, and 5_1 are allocated to compare the partitions
of task 1_1 intermediate results (R1-1_1 through R1-1_z) with
partitions of task 1-5 intermediate results partitions (R1-5_1
through R1-5_z) to produce task 1_6 intermediate results (R1-6,
which is the list translation errors due to non-words).
Task 1_7 (e.g., determine words correctly translated) is ordered
after tasks 1_2 and 1_5 and is to be executed on tasks 1_2's and
1_5's intermediate results (R1-1 and R1-5). DT execution modules
1_2, 2_2, 3_2, 4_2, and 5_2 are allocated to compare the partitions
of task 1_2 intermediate results (R1-2_1 through R1-2_z) with
partitions of task 1-5 intermediate results partitions (R1-5_1
through R1-5_z) to produce task 1_7 intermediate results (R1-7,
which is the list of correctly translated words).
Task 2 (e.g., find specific words and/or phrases) has no task
ordering (i.e., is independent of the results of other sub-tasks),
is to be performed on data partitions 2_1 through 2_z by DT
execution modules 3_1, 4_1, 5_1, 6_1, and 7_1. For instance, DT
execution modules 3_1, 4_1, 5_1, 6_1, and 7_1 search for specific
words and/or phrases in data partitions 2_1 through 2_z to produce
task 2 intermediate results (R2, which is a list of specific words
and/or phrases).
Task 3_2 (e.g., find specific translated words and/or phrases) is
ordered after task 1_3 (e.g., translate) is to be performed on
partitions R1-3_1 through R1-3_z by DT execution modules 1_2, 2_2,
3_2, 4_2, and 5_2. For instance, DT execution modules 1_2, 2_2,
3_2, 4_2, and 5_2 search for specific translated words and/or
phrases in the partitions of the translated data (R1-3_1 through
R1-3_z) to produce task 3_2 intermediate results (R3-2, which is a
list of specific translated words and/or phrases).
For each task, the intermediate result information indicates which
DST unit is responsible for overseeing execution of the task and,
if needed, processing the partial results generated by the set of
allocated DT execution units. In addition, the intermediate result
information indicates a scratch pad memory for the task and where
the corresponding intermediate results are to be stored. For
example, for intermediate result R1-1 (the intermediate result of
task 1_1), DST unit 1 is responsible for overseeing execution of
the task 1_1 and coordinates storage of the intermediate result as
encoded intermediate result slices stored in memory of DST
execution units 1-5. In general, the scratch pad is for storing
non-DS encoded intermediate results and the intermediate result
storage is for storing DS encoded intermediate results.
FIGS. 33-38 are schematic block diagrams of the distributed storage
and task network (DSTN) module performing the example of FIG. 30.
In FIG. 33, the DSTN module accesses the data 92 and partitions it
into a plurality of partitions 1-z in accordance with distributed
storage and task network (DST) allocation information. For each
data partition, the DSTN identifies a set of its DT (distributed
task) execution modules 90 to perform the task (e.g., identify
non-words (i.e., not in a reference dictionary) within the data
partition) in accordance with the DST allocation information. From
data partition to data partition, the set of DT execution modules
90 may be the same, different, or a combination thereof (e.g., some
data partitions use the same set while other data partitions use
different sets).
For the first data partition, the first set of DT execution modules
(e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DST allocation
information of FIG. 32) executes task 1_1 to produce a first
partial result 102 of non-words found in the first data partition.
The second set of DT execution modules (e.g., 1_1, 2_1, 3_1, 4_1,
and 5_1 per the DST allocation information of FIG. 32) executes
task 1_1 to produce a second partial result 102 of non-words found
in the second data partition. The sets of DT execution modules (as
per the DST allocation information) perform task 1_1 on the data
partitions until the "z" set of DT execution modules performs task
1_1 on the "zth" data partition to produce a "zth" partial result
102 of non-words found in the "zth" data partition.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 1 is assigned to process the first through "zth"
partial results to produce the first intermediate result (R1-1),
which is a list of non-words found in the data. For instance, each
set of DT execution modules 90 stores its respective partial result
in the scratchpad memory of DST execution unit 1 (which is
identified in the DST allocation or may be determined by DST
execution unit 1). A processing module of DST execution 1 is
engaged to aggregate the first through "zth" partial results to
produce the first intermediate result (e.g., R1_1). The processing
module stores the first intermediate result as non-DS error encoded
data in the scratchpad memory or in another section of memory of
DST execution unit 1.
DST execution unit 1 engages its DST client module to slice
grouping based DS error encode the first intermediate result (e.g.,
the list of non-words). To begin the encoding, the DST client
module determines whether the list of non-words is of a sufficient
size to partition (e.g., greater than a Terabyte). If yes, it
partitions the first intermediate result (R1-1) into a plurality of
partitions (e.g., R1-1_1 through R1-1_m). If the first intermediate
result is not of sufficient size to partition, it is not
partitioned.
For each partition of the first intermediate result, or for the
first intermediate result, the DST client module uses the DS error
encoding parameters of the data (e.g., DS parameters of data 2,
which includes 3/5 decode threshold/pillar width ratio) to produce
slice groupings. The slice groupings are stored in the intermediate
result memory (e.g., allocated memory in the memories of DST
execution units 1-5).
In FIG. 34, the DSTN module is performing task 1_2 (e.g., find
unique words) on the data 92. To begin, the DSTN module accesses
the data 92 and partitions it into a plurality of partitions 1-z in
accordance with the DST allocation information or it may use the
data partitions of task 1_1 if the partitioning is the same. For
each data partition, the DSTN identifies a set of its DT execution
modules to perform task 1_2 in accordance with the DST allocation
information. From data partition to data partition, the set of DT
execution modules may be the same, different, or a combination
thereof. For the data partitions, the allocated set of DT execution
modules executes task 1_2 to produce a partial results (e.g.,
1.sup.st through "zth") of unique words found in the data
partitions.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 1 is assigned to process the first through "zth"
partial results 102 of task 1_2 to produce the second intermediate
result (R1-2), which is a list of unique words found in the data
92. The processing module of DST execution 1 is engaged to
aggregate the first through "zth" partial results of unique words
to produce the second intermediate result. The processing module
stores the second intermediate result as non-DS error encoded data
in the scratchpad memory or in another section of memory of DST
execution unit 1.
DST execution unit 1 engages its DST client module to slice
grouping based DS error encode the second intermediate result
(e.g., the list of non-words). To begin the encoding, the DST
client module determines whether the list of unique words is of a
sufficient size to partition (e.g., greater than a Terabyte). If
yes, it partitions the second intermediate result (R1-2) into a
plurality of partitions (e.g., R1-2_1 through R1-2_m). If the
second intermediate result is not of sufficient size to partition,
it is not partitioned.
For each partition of the second intermediate result, or for the
second intermediate results, the DST client module uses the DS
error encoding parameters of the data (e.g., DS parameters of data
2, which includes 3/5 decode threshold/pillar width ratio) to
produce slice groupings. The slice groupings are stored in the
intermediate result memory (e.g., allocated memory in the memories
of DST execution units 1-5).
In FIG. 35, the DSTN module is performing task 1_3 (e.g.,
translate) on the data 92. To begin, the DSTN module accesses the
data 92 and partitions it into a plurality of partitions 1-z in
accordance with the DST allocation information or it may use the
data partitions of task 1_1 if the partitioning is the same. For
each data partition, the DSTN identifies a set of its DT execution
modules to perform task 1_3 in accordance with the DST allocation
information (e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1
translate data partitions 2_1 through 2_4 and DT execution modules
1_2, 2_2, 3_2, 4_2, and 5_2 translate data partitions 2_5 through
2_z). For the data partitions, the allocated set of DT execution
modules 90 executes task 1_3 to produce partial results 102 (e.g.,
1.sup.st through "zth") of translated data.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 2 is assigned to process the first through "zth"
partial results of task 1_3 to produce the third intermediate
result (R1-3), which is translated data. The processing module of
DST execution 2 is engaged to aggregate the first through "zth"
partial results of translated data to produce the third
intermediate result. The processing module stores the third
intermediate result as non-DS error encoded data in the scratchpad
memory or in another section of memory of DST execution unit 2.
DST execution unit 2 engages its DST client module to slice
grouping based DS error encode the third intermediate result (e.g.,
translated data). To begin the encoding, the DST client module
partitions the third intermediate result (R1-3) into a plurality of
partitions (e.g., R1-3_1 through R1-3_y). For each partition of the
third intermediate result, the DST client module uses the DS error
encoding parameters of the data (e.g., DS parameters of data 2,
which includes 3/5 decode threshold/pillar width ratio) to produce
slice groupings. The slice groupings are stored in the intermediate
result memory (e.g., allocated memory in the memories of DST
execution units 2-6 per the DST allocation information).
As is further shown in FIG. 35, the DSTN module is performing task
1_4 (e.g., retranslate) on the translated data of the third
intermediate result. To begin, the DSTN module accesses the
translated data (from the scratchpad memory or from the
intermediate result memory and decodes it) and partitions it into a
plurality of partitions in accordance with the DST allocation
information. For each partition of the third intermediate result,
the DSTN identifies a set of its DT execution modules 90 to perform
task 1_4 in accordance with the DST allocation information (e.g.,
DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 are allocated to
translate back partitions R1-3_1 through R1-3_4 and DT execution
modules 1_2, 2_2, 6_1, 7_1, and 7_2 are allocated to translate back
partitions R1-3_5 through R1-3_z). For the partitions, the
allocated set of DT execution modules executes task 1_4 to produce
partial results 102 (e.g., 1.sup.st through "zth") of re-translated
data.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 3 is assigned to process the first through "zth"
partial results of task 1_4 to produce the fourth intermediate
result (R1-4), which is retranslated data. The processing module of
DST execution 3 is engaged to aggregate the first through "zth"
partial results of retranslated data to produce the fourth
intermediate result. The processing module stores the fourth
intermediate result as non-DS error encoded data in the scratchpad
memory or in another section of memory of DST execution unit 3.
DST execution unit 3 engages its DST client module to slice
grouping based DS error encode the fourth intermediate result
(e.g., retranslated data). To begin the encoding, the DST client
module partitions the fourth intermediate result (R1-4) into a
plurality of partitions (e.g., R1-4_1 through R1-4_z). For each
partition of the fourth intermediate result, the DST client module
uses the DS error encoding parameters of the data (e.g., DS
parameters of data 2, which includes 3/5 decode threshold/pillar
width ratio) to produce slice groupings. The slice groupings are
stored in the intermediate result memory (e.g., allocated memory in
the memories of DST execution units 3-7 per the DST allocation
information).
In FIG. 36, a distributed storage and task network (DSTN) module is
performing task 1_5 (e.g., compare) on data 92 and retranslated
data of FIG. 35. To begin, the DSTN module accesses the data 92 and
partitions it into a plurality of partitions in accordance with the
DST allocation information or it may use the data partitions of
task 1_1 if the partitioning is the same. The DSTN module also
accesses the retranslated data from the scratchpad memory, or from
the intermediate result memory and decodes it, and partitions it
into a plurality of partitions in accordance with the DST
allocation information. The number of partitions of the
retranslated data corresponds to the number of partitions of the
data.
For each pair of partitions (e.g., data partition 1 and
retranslated data partition 1), the DSTN identifies a set of its DT
execution modules 90 to perform task 1_5 in accordance with the DST
allocation information (e.g., DT execution modules 1_1, 2_1, 3_1,
4_1, and 5_1). For each pair of partitions, the allocated set of DT
execution modules executes task 1_5 to produce partial results 102
(e.g., 1.sup.st through "zth") of a list of incorrectly translated
words and/or phrases.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 1 is assigned to process the first through "zth"
partial results of task 1_5 to produce the fifth intermediate
result (R1-5), which is the list of incorrectly translated words
and/or phrases. In particular, the processing module of DST
execution 1 is engaged to aggregate the first through "zth" partial
results of the list of incorrectly translated words and/or phrases
to produce the fifth intermediate result. The processing module
stores the fifth intermediate result as non-DS error encoded data
in the scratchpad memory or in another section of memory of DST
execution unit 1.
DST execution unit 1 engages its DST client module to slice
grouping based DS error encode the fifth intermediate result. To
begin the encoding, the DST client module partitions the fifth
intermediate result (R1-5) into a plurality of partitions (e.g.,
R1-5_1 through R1-5_z). For each partition of the fifth
intermediate result, the DST client module uses the DS error
encoding parameters of the data (e.g., DS parameters of data 2,
which includes 3/5 decode threshold/pillar width ratio) to produce
slice groupings. The slice groupings are stored in the intermediate
result memory (e.g., allocated memory in the memories of DST
execution units 1-5 per the DST allocation information).
As is further shown in FIG. 36, the DSTN module is performing task
1_6 (e.g., translation errors due to non-words) on the list of
incorrectly translated words and/or phrases (e.g., the fifth
intermediate result R1-5) and the list of non-words (e.g., the
first intermediate result R1-1). To begin, the DSTN module accesses
the lists and partitions them into a corresponding number of
partitions.
For each pair of partitions (e.g., partition R1-1_1 and partition
R1-5_1), the DSTN identifies a set of its DT execution modules 90
to perform task 1_6 in accordance with the DST allocation
information (e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and
5_1). For each pair of partitions, the allocated set of DT
execution modules executes task 1_6 to produce partial results 102
(e.g., 1.sup.st through "zth") of a list of incorrectly translated
words and/or phrases due to non-words.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 2 is assigned to process the first through "zth"
partial results of task 1_6 to produce the sixth intermediate
result (R1-6), which is the list of incorrectly translated words
and/or phrases due to non-words. In particular, the processing
module of DST execution 2 is engaged to aggregate the first through
"zth" partial results of the list of incorrectly translated words
and/or phrases due to non-words to produce the sixth intermediate
result. The processing module stores the sixth intermediate result
as non-DS error encoded data in the scratchpad memory or in another
section of memory of DST execution unit 2.
DST execution unit 2 engages its DST client module to slice
grouping based DS error encode the sixth intermediate result. To
begin the encoding, the DST client module partitions the sixth
intermediate result (R1-6) into a plurality of partitions (e.g.,
R1-6_1 through R1-6_z). For each partition of the sixth
intermediate result, the DST client module uses the DS error
encoding parameters of the data (e.g., DS parameters of data 2,
which includes 3/5 decode threshold/pillar width ratio) to produce
slice groupings. The slice groupings are stored in the intermediate
result memory (e.g., allocated memory in the memories of DST
execution units 2-6 per the DST allocation information).
As is still further shown in FIG. 36, the DSTN module is performing
task 1_7 (e.g., correctly translated words and/or phrases) on the
list of incorrectly translated words and/or phrases (e.g., the
fifth intermediate result R1-5) and the list of unique words (e.g.,
the second intermediate result R1-2). To begin, the DSTN module
accesses the lists and partitions them into a corresponding number
of partitions.
For each pair of partitions (e.g., partition R1-2_1 and partition
R1-5_1), the DSTN identifies a set of its DT execution modules 90
to perform task 1_7 in accordance with the DST allocation
information (e.g., DT execution modules 1_2, 2_2, 3_2, 4_2, and
5_2). For each pair of partitions, the allocated set of DT
execution modules executes task 1_7 to produce partial results 102
(e.g., 1.sup.st through "zth") of a list of correctly translated
words and/or phrases.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 3 is assigned to process the first through "zth"
partial results of task 1_7 to produce the seventh intermediate
result (R1-7), which is the list of correctly translated words
and/or phrases. In particular, the processing module of DST
execution 3 is engaged to aggregate the first through "zth" partial
results of the list of correctly translated words and/or phrases to
produce the seventh intermediate result. The processing module
stores the seventh intermediate result as non-DS error encoded data
in the scratchpad memory or in another section of memory of DST
execution unit 3.
DST execution unit 3 engages its DST client module to slice
grouping based DS error encode the seventh intermediate result. To
begin the encoding, the DST client module partitions the seventh
intermediate result (R1-7) into a plurality of partitions (e.g.,
R1-7_1 through R1-7_z). For each partition of the seventh
intermediate result, the DST client module uses the DS error
encoding parameters of the data (e.g., DS parameters of data 2,
which includes 3/5 decode threshold/pillar width ratio) to produce
slice groupings. The slice groupings are stored in the intermediate
result memory (e.g., allocated memory in the memories of DST
execution units 3-7 per the DST allocation information).
In FIG. 37, the distributed storage and task network (DSTN) module
is performing task 2 (e.g., find specific words and/or phrases) on
the data 92. To begin, the DSTN module accesses the data and
partitions it into a plurality of partitions 1-z in accordance with
the DST allocation information or it may use the data partitions of
task 1_1 if the partitioning is the same. For each data partition,
the DSTN identifies a set of its DT execution modules 90 to perform
task 2 in accordance with the DST allocation information. From data
partition to data partition, the set of DT execution modules may be
the same, different, or a combination thereof. For the data
partitions, the allocated set of DT execution modules executes task
2 to produce partial results 102 (e.g., 1.sup.st through "zth") of
specific words and/or phrases found in the data partitions.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 7 is assigned to process the first through "zth"
partial results of task 2 to produce task 2 intermediate result
(R2), which is a list of specific words and/or phrases found in the
data. The processing module of DST execution 7 is engaged to
aggregate the first through "zth" partial results of specific words
and/or phrases to produce the task 2 intermediate result. The
processing module stores the task 2 intermediate result as non-DS
error encoded data in the scratchpad memory or in another section
of memory of DST execution unit 7.
DST execution unit 7 engages its DST client module to slice
grouping based DS error encode the task 2 intermediate result. To
begin the encoding, the DST client module determines whether the
list of specific words and/or phrases is of a sufficient size to
partition (e.g., greater than a Terabyte). If yes, it partitions
the task 2 intermediate result (R2) into a plurality of partitions
(e.g., R2_1 through R2_m). If the task 2 intermediate result is not
of sufficient size to partition, it is not partitioned.
For each partition of the task 2 intermediate result, or for the
task 2 intermediate results, the DST client module uses the DS
error encoding parameters of the data (e.g., DS parameters of data
2, which includes 3/5 decode threshold/pillar width ratio) to
produce slice groupings. The slice groupings are stored in the
intermediate result memory (e.g., allocated memory in the memories
of DST execution units 1-4, and 7).
In FIG. 38, the distributed storage and task network (DSTN) module
is performing task 3 (e.g., find specific translated words and/or
phrases) on the translated data (R1-3). To begin, the DSTN module
accesses the translated data (from the scratchpad memory or from
the intermediate result memory and decodes it) and partitions it
into a plurality of partitions in accordance with the DST
allocation information. For each partition, the DSTN identifies a
set of its DT execution modules to perform task 3 in accordance
with the DST allocation information. From partition to partition,
the set of DT execution modules may be the same, different, or a
combination thereof. For the partitions, the allocated set of DT
execution modules 90 executes task 3 to produce partial results 102
(e.g., 1.sup.st through "zth") of specific translated words and/or
phrases found in the data partitions.
As indicated in the DST allocation information of FIG. 32, DST
execution unit 5 is assigned to process the first through "zth"
partial results of task 3 to produce task 3 intermediate result
(R3), which is a list of specific translated words and/or phrases
found in the translated data. In particular, the processing module
of DST execution 5 is engaged to aggregate the first through "zth"
partial results of specific translated words and/or phrases to
produce the task 3 intermediate result. The processing module
stores the task 3 intermediate result as non-DS error encoded data
in the scratchpad memory or in another section of memory of DST
execution unit 7.
DST execution unit 5 engages its DST client module to slice
grouping based DS error encode the task 3 intermediate result. To
begin the encoding, the DST client module determines whether the
list of specific translated words and/or phrases is of a sufficient
size to partition (e.g., greater than a Terabyte). If yes, it
partitions the task 3 intermediate result (R3) into a plurality of
partitions (e.g., R3_1 through R3_m). If the task 3 intermediate
result is not of sufficient size to partition, it is not
partitioned.
For each partition of the task 3 intermediate result, or for the
task 3 intermediate results, the DST client module uses the DS
error encoding parameters of the data (e.g., DS parameters of data
2, which includes 3/5 decode threshold/pillar width ratio) to
produce slice groupings. The slice groupings are stored in the
intermediate result memory (e.g., allocated memory in the memories
of DST execution units 1-4, 5, and 7).
FIG. 39 is a diagram of an example of combining result information
into final results 104 for the example of FIG. 30. In this example,
the result information includes the list of specific words and/or
phrases found in the data (task 2 intermediate result), the list of
specific translated words and/or phrases found in the data (task 3
intermediate result), the list of non-words found in the data (task
1 first intermediate result R1-1), the list of unique words found
in the data (task 1 second intermediate result R1-2), the list of
translation errors due to non-words (task 1 sixth intermediate
result R1-6), and the list of correctly translated words and/or
phrases (task 1 seventh intermediate result R1-7). The task
distribution module provides the result information to the
requesting DST client module as the results 104.
FIG. 40A is a schematic block diagram of an embodiment of a
decentralized agreement module 350 that includes a set of
deterministic functions 1-N, a set of normalizing functions 1-N, a
set of scoring functions 1-N, and a ranking function 352. Each of
the deterministic function, the normalizing function, the scoring
function, and the ranking function 352, may be implemented
utilizing the processing module 84 of FIG. 3. The decentralized
agreement module 350 may be implemented utilizing any module and/or
unit of a dispersed storage network (DSN). For example, the
decentralized agreement module is implemented utilizing the
distributed storage and task (DST) client module 34 of FIG. 1.
The decentralized agreement module 350 functions to receive a
ranked scoring information request 354 and to generate ranked
scoring information 358 based on the ranked scoring information
request 354 and other information. The ranked scoring information
request 354 includes one or more of an asset identifier (ID) 356 of
an asset associated with the request, an asset type indicator, one
or more location identifiers of locations associated with the DSN,
one or more corresponding location weights, and a requesting entity
ID. The asset includes any portion of data associated with the DSN
including one or more asset types including a data object, a data
record, an encoded data slice, a data segment, a set of encoded
data slices, and a plurality of sets of encoded data slices. As
such, the asset ID 356 of the asset includes one or more of a data
name, a data record identifier, a source name, a slice name, and a
plurality of sets of slice names.
Each location of the DSN includes an aspect of a DSN resource.
Examples of locations includes one or more of a storage unit, a
memory device of the storage unit, a site, a storage pool of
storage units, a pillar index associated with each encoded data
slice of a set of encoded data slices generated by an information
dispersal algorithm (IDA), a DST client module 34 of FIG. 1, a DST
processing unit 16 of FIG. 1, a DST integrity processing unit 20 of
FIG. 1, a DSTN managing unit 18 of FIG. 1, a user device 12 of FIG.
1, and a user device 14 of FIG. 1.
Each location is associated with a location weight based on one or
more of a resource prioritization of utilization scheme and
physical configuration of the DSN. The location weight includes an
arbitrary bias which adjusts a proportion of selections to an
associated location such that a probability that an asset will be
mapped to that location is equal to the location weight divided by
a sum of all location weights for all locations of comparison. For
example, each storage pool of a plurality of storage pools is
associated with a location weight based on storage capacity. For
instance, storage pools with more storage capacity are associated
with higher location weights than others. The other information may
include a set of location identifiers and a set of location weights
associated with the set of location identifiers. For example, the
other information includes location identifiers and location
weights associated with a set of memory devices of a storage unit
when the requesting entity utilizes the decentralized agreement
module 350 to produce ranked scoring information 358 with regards
to selection of a memory device of the set of memory devices for
accessing a particular encoded data slice (e.g., where the asset ID
includes a slice name of the particular encoded data slice).
The decentralized agreement module 350 outputs substantially
identical ranked scoring information for each ranked scoring
information request that includes substantially identical content
of the ranked scoring information request. For example, a first
requesting entity issues a first ranked scoring information request
to the decentralized agreement module 350 and receives first ranked
scoring information. A second requesting entity issues a second
ranked scoring information request to the decentralized agreement
module and receives second ranked scoring information. The second
ranked scoring information is substantially the same as the first
ranked scoring information when the second ranked scoring
information request is substantially the same as the first ranked
scoring information request.
As such, two or more requesting entities may utilize the
decentralized agreement module 350 to determine substantially
identical ranked scoring information. As a specific example, the
first requesting entity selects a first storage pool of a plurality
of storage pools for storing a set of encoded data slices utilizing
the decentralized agreement module 350 and the second requesting
entity identifies the first storage pool of the plurality of
storage pools for retrieving the set of encoded data slices
utilizing the decentralized agreement module 350.
In an example of operation, the decentralized agreement module 350
receives the ranked scoring information request 354. Each
deterministic function performs a deterministic function on a
combination and/or concatenation (e.g., add, append, interleave) of
the asset ID 356 of the ranked scoring information request 354 and
an associated location ID of the set of location IDs to produce an
interim result. The deterministic function includes at least one of
a hashing function, a hash-based message authentication code
function, a mask generating function, a cyclic redundancy code
function, hashing module of a number of locations, consistent
hashing, rendezvous hashing, and a sponge function. As a specific
example, deterministic function 2 appends a location ID 2 of a
storage pool 2 to a source name as the asset ID to produce a
combined value and performs the mask generating function on the
combined value to produce interim result 2.
With a set of interim results 1-N, each normalizing function
performs a normalizing function on a corresponding interim result
to produce a corresponding normalized interim result. The
performing of the normalizing function includes dividing the
interim result by a number of possible permutations of the output
of the deterministic function to produce the normalized interim
result. For example, normalizing function 2 performs the
normalizing function on the interim result 2 to produce a
normalized interim result 2.
With a set of normalized interim results 1-N, each scoring function
performs a scoring function on a corresponding normalized interim
result to produce a corresponding score. The performing of the
scoring function includes dividing an associated location weight by
a negative log of the normalized interim result. For example,
scoring function 2 divides location weight 2 of the storage pool 2
(e.g., associated with location ID 2) by a negative log of the
normalized interim result 2 to produce a score 2.
With a set of scores 1-N, the ranking function 352 performs a
ranking function on the set of scores 1-N to generate the ranked
scoring information 358. The ranking function includes rank
ordering each score with other scores of the set of scores 1-N,
where a highest score is ranked first. As such, a location
associated with the highest score may be considered a highest
priority location for resource utilization (e.g., accessing,
storing, retrieving, etc., the given asset of the request). Having
generated the ranked scoring information 358, the decentralized
agreement module 350 outputs the ranked scoring information 358 to
the requesting entity.
FIG. 40B is a flowchart illustrating an example of selecting a
resource. The method begins or continues at step 360 where a
processing module (e.g., of a decentralized agreement module)
receives a ranked scoring information request from a requesting
entity with regards to a set of candidate resources. For each
candidate resource, the method continues at step 362 where the
processing module performs a deterministic function on a location
identifier (ID) of the candidate resource and an asset ID of the
ranked scoring information request to produce an interim result. As
a specific example, the processing module combines the asset ID and
the location ID of the candidate resource to produce a combined
value and performs a hashing function on the combined value to
produce the interim result.
For each interim result, the method continues at step 364 where the
processing module performs a normalizing function on the interim
result to produce a normalized interim result. As a specific
example, the processing module obtains a permutation value
associated with the deterministic function (e.g., maximum number of
permutations of output of the deterministic function) and divides
the interim result by the permutation value to produce the
normalized interim result (e.g., with a value between 0 and 1).
For each normalized interim result, the method continues at step
366 where the processing module performs a scoring function on the
normalized interim result utilizing a location weight associated
with the candidate resource associated with the interim result to
produce a score of a set of scores. As a specific example, the
processing module divides the location weight by a negative log of
the normalized interim result to produce the score.
The method continues at step 368 where the processing module rank
orders the set of scores to produce ranked scoring information
(e.g., ranking a highest value first). The method continues at step
370 where the processing module outputs the ranked scoring
information to the requesting entity. The requesting entity may
utilize the ranked scoring information to select one location of a
plurality of locations.
FIG. 40C is a schematic block diagram of an embodiment of a
dispersed storage network (DSN) that includes the distributed
storage and task (DST) processing unit 16 of FIG. 1, the network 24
of FIG. 1, and the distributed storage and task network (DSTN)
module 22 of FIG. 1. Hereafter, the DSTN module 22 may be
interchangeably referred to as a DSN memory. The DST processing
unit 16 includes a decentralized agreement module 380 and the DST
client module 34 of FIG. 1. The decentralized agreement module 380
be implemented utilizing the decentralized agreement module 350 of
FIG. 40A. The DSTN module 22 includes a plurality of DST execution
(EX) unit pools 1-P. Each DST execution unit pool includes a one or
more sites 1-S. Each site includes one or more DST execution units
1-N. Each DST execution unit may be associated with at least one
pillar of N pillars associated with an information dispersal
algorithm (IDA), where a data segment is dispersed storage error
encoded using the IDA to produce one or more sets of encoded data
slices, and where each set includes N encoded data slices and like
encoded data slices (e.g., slice 3's) of two or more sets of
encoded data slices are included in a common pillar (e.g., pillar
3). Each site may not include every pillar and a given pillar may
be implemented at more than one site. Each DST execution unit
includes a plurality of memories 1-M. Each DST execution unit may
be implemented utilizing the DST execution unit 36 of FIG. 1.
Hereafter, a DST execution unit may be referred to interchangeably
as a storage unit and a set of DST execution units may be
interchangeably referred to as a set of storage units and/or as a
storage unit set.
The DSN functions to receive data access requests 382, select
resources of at least one DST execution unit pool for data access,
utilize the selected DST execution unit pool for the data access,
and issue a data access response 392 based on the data access. The
selecting of the resources includes utilizing a decentralized
agreement function of the decentralized agreement module 380, where
a plurality of locations are ranked against each other. The
selecting may include selecting one storage pool of the plurality
of storage pools, selecting DST execution units at various sites of
the plurality of sites, selecting a memory of the plurality of
memories for each DST execution unit, and selecting combinations of
memories, DST execution units, sites, pillars, and storage
pools.
In an example of operation, the DST client module 34 receives the
data access request 382 from a requesting entity, where the data
access request 382 includes at least one of a store data request, a
retrieve data request, a delete data request, a data name, and a
requesting entity identifier (ID). Having received the data access
request 382, the DST client module 34 determines a DSN address
associated with the data access request. The DSN address includes
at least one of a source name (e.g., including a vault ID and an
object number associated with the data name), a data segment ID, a
set of slice names, a plurality of sets of slice names. The
determining includes at least one of generating (e.g., for the
store data request) and retrieving (e.g., from a DSN directory,
from a dispersed hierarchical index) based on the data name (e.g.,
for the retrieve data request).
Having determined the DSN address, the DST client module 34 selects
a plurality of resource levels (e.g., DST EX unit pool, site, DST
execution unit, pillar, memory) associated with the DSTN module 22.
The determining may be based on one or more of the data name, the
requesting entity ID, a predetermination, a lookup, a DSN
performance indicator, and interpreting an error message. For
example, the DST client module 34 selects the DST execution unit
pool as a first resource level and a set of memory devices of a
plurality of memory devices as a second resource level based on a
system registry lookup for a vault associated with the requesting
entity.
Having selected the plurality resource levels, the DST client
module 34, for each resource level, issues a ranked scoring
information request 384 to the decentralized agreement module 380
utilizing the DSN address as an asset ID. The decentralized
agreement module 380 performs the decentralized agreement function
based on the asset ID (e.g., the DSN address), identifiers of
locations of the selected resource levels, and location weights of
the locations to generate ranked scoring information 386.
For each resource level, the DST client module 34 receives
corresponding ranked scoring information 386. Having received the
ranked scoring information 386, the DST client module 34 identifies
one or more resources associated with the resource level based on
the rank scoring information 386. For example, the DST client
module 34 identifies a DST execution unit pool associated with a
highest score and identifies a set of memory devices within DST
execution units of the identified DST execution unit pool with a
highest score.
Having identified the one or more resources, the DST client module
34 accesses the DSTN module 22 based on the identified one or more
resources associated with each resource level. For example, the DST
client module 34 issues resource access requests 388 (e.g., write
slice requests when storing data, read slice requests when
recovering data) to the identified DST execution unit pool, where
the resource access requests 388 further identify the identified
set of memory devices. Having accessed the DSTN module 22, the DST
client module 34 receives resource access responses 390 (e.g.,
write slice responses, read slice responses). The DST client module
34 issues the data access response 392 based on the received
resource access responses 390. For example, the DST client module
34 decodes received encoded data slices to reproduce data and
generates the data access response 392 to include the reproduced
data.
FIG. 40D is a flowchart illustrating an example of accessing a
dispersed storage network (DSN) memory. The method begins or
continues at step 394 where a processing module (e.g., of a
distributed storage and task (DST) client module) receives a data
access request from a requesting entity. The data access request
includes one or more of a storage request, a retrieval request, a
requesting entity identifier, and a data identifier (ID). The
method continues at step 396 where the processing module determines
a DSN address associated with the data access request. For example,
the processing module generates the DSN address for the storage
request. As another example, the processing module performs a
lookup for the retrieval request based on the data identifier.
The method continues at step 398 where the processing module
selects a plurality resource levels associated with the DSN memory.
The selecting may be based on one or more of a predetermination, a
range of weights associated with available resources, a resource
performance level, and a resource performance requirement level.
For each resource level, the method continues at step 400 where the
processing module determines ranked scoring information. For
example, the processing module issues a ranked scoring information
request to a decentralized agreement module based on the DSN
address and receives corresponding ranked scoring information for
the resource level, where the decentralized agreement module
performs a decentralized agreement protocol function on the DSN
address using the associated resource identifiers and resource
weights for the resource level to produce the ranked scoring
information for the resource level.
For each resource level, the method continues at step 402 where the
processing module selects one or more resources associated with the
resource level based on the ranked scoring information. For
example, the processing module selects a resource associated with a
highest score when one resource is required. As another example,
the processing module selects a plurality of resources associated
with highest scores when a plurality of resources are required.
The method continues at step 404 where the processing module
accesses the DSN memory utilizing the selected one or more
resources for each of the plurality of resource levels. For
example, the processing module identifies network addressing
information based on the selected resources including one or more
of a storage unit Internet protocol address and a memory device
identifier, generates a set of encoded data slice access requests
based on the data access request and the DSN address, and sends the
set of encoded data slice access requests to the DSN memory
utilizing the identified network addressing information.
The method continues at step 406 where the processing module issues
a data access response to the requesting entity based on one or
more resource access responses from the DSN memory. For example,
the processing module issues a data storage status indicator when
storing data. As another example, the processing module generates
the data access response to include recovered data when retrieving
data.
FIG. 41A is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) that includes a set of distributed
storage and task (DST) execution units 1-n and the network 24 of
FIG. 1. Each DST execution unit includes a decentralized agreement
module 410, the DST client module 34 of FIG. 1, and a plurality of
memories 1-60. Each decentralized agreement module 410 may be
implemented utilizing the decentralized agreement module 350 of
FIG. 40A. Each memory may be implemented utilizing the memory 88 of
FIG. 3.
The DSN functions to provide access to data stored as a plurality
of sets of encoded data slices in the set of DST execution units
and to rebuild encoded data slices associated with storage errors.
In an example of operation of accessing the data, a DST client
module 34 of a DST execution unit receives a slice access request
that includes a slice name of an encoded data slice. Having
received the slice name, the DST client module 34 identifies a
range of DSN addresses of a plurality of ranges of DSN addresses
associated with the DST execution unit (e.g., received, look up),
where the range of DSN addresses includes a slice name. For
example, each DST execution unit is associated with 10 DSN ranges,
where each DSN address range is mapped to a subset of the plurality
of memories. For instance, a second DSN address range is mapped to
memories 7-12.
Having identified the range of DSN addresses, the DST client module
34 identifies a memory device of a corresponding subset of the
plurality of memories using a decentralized agreement function
based on the slice name and current location weights of each memory
device of the subset of memory devices. For example, the DST client
module 34 issues a ranked scoring information request 414 to the
decentralized agreement module 410, receives the ranked scoring
information 416, and identifies a memory device associated with a
highest score.
Having identified the memory device, the DST client module 34
facilitates the slice access request with the identified memory
device. For example, the DST client module 34 retrieves the encoded
data slice from the identified memory device and sends the
retrieved encoded data slice to a requesting entity when the slice
access request includes a retrieve slice request. As another
example, the DST client module 34 stores an encoded data slice of
the slice access request into the identified memory device when the
slice access request includes a store slice request.
In an example of operation of the rebuilding, the DST client module
34 detects a failed memory device within an associated subset of
memory devices. The detecting includes at least one of interpreting
an error message, performing a memory test, and interpreting a
memory test result. Having detected the failed memory device, the
DST client module 34 identifies the DSN address range associated
with the subset of memory devices (e.g., a lookup). Having
identified the DSN address range, the DST client module 34
facilitates rebuilding for the identified DSN address range by
accessing the subset of memory devices, issuing rebuilding messages
412 to other DST execution units of the set of DST execution units,
receiving further rebuilding messages 412 from the other DST
execution units, identifying a missing encoded data slices of the
subset of memory devices, and generating rebuilt encoded data
slices.
Having facilitated the rebuilding, the DST client module 34 updates
location weights of the subset of memory devices based on the
failure. For example, the DST client module 34 zeros out location
weight of the failed memory device and raises location weights of
remaining memory devices of the subset of memory devices that
includes the failed memory device. Having updated the location
weights, the DST client module 34 facilitates storage of the
rebuilt encoded data slices utilizing the decentralized agreement
function based on corresponding slice names and the updated
location weights of the memory devices of the subset of memory
devices.
FIG. 41B is a flowchart illustrating an example of accessing and
rebuilding encoded data slices. The method begins or continues,
when accessing an encoded data slice, at step 420 where a
processing module (e.g., of a distributed storage and task (DST)
client module of a storage unit) receives a slice access request
that includes a slice name. The method continues at step 422 where
the processing module identifies a sub-range of a DSN address range
associated with the storage unit. For example, the processing
module accesses a slice name to sub-range table. As another
example, the processing module performs a deterministic function on
the slice name to produce the sub-range.
The method continues at step 424 where the processing module
identifies a memory device of a group of memory devices associated
with the sub-range utilizing a decentralized agreement function
based on the slice name. For example, the processing module
performs the decentralized agreement function to produce scores for
each of the memory devices of a group of memory devices using one
or more of location weights of each memory device, the slice name,
and a memory group identifier. The method continues at step 426
where the processing module facilitates a slice access request with
the identified memory device (e.g., store, retrieve, delete,
list).
The method begins or continues, when rebuilding, at step 428 where
the processing module detects a storage error associated with a
memory device of the group of memory devices. The detecting
includes one or more of receiving an error message, performing a
memory device test, interpreting a memory device test result,
detecting a corrupted slice, detecting a failed memory, and
detecting a missing slice. The method continues at step 430 where
the processing module identifies the sub-range of the DSN address
range associated with a group of memory devices. For example, the
processing module accesses the slice name to sub-range table using
an identifier of the memory device.
The method continues at step 432 where the processing module
facilitates rebuilding of the identified sub-range to produce
rebuilt encoded data slices. The facilitating includes one or more
of scanning for missing slices across the sub-range, acquiring a
decode threshold number of slices for each missing slice, and
generating rebuilt slices from the acquired slices. The method
continues at step 434 where the processing module updates location
weights of the group of memory devices based on the detected
storage error. For example, the processing module updates a
location weight for the failed memory device to zero and raises
location weights for remaining memory devices of a group of memory
devices in a total amount equivalent to a previous location weight
for the failed memory device.
For each rebuilt encoded data slice, the method continues at step
436 where the processing module identifies a corresponding memory
device of the group of memory devices for storage of the rebuilt
encoded data slice utilizing the decentralized agreement function
and the updated location weights. For example, the processing
module performs the decentralized agreement function for each of
the memory devices using updated location weights, a slice name of
the rebuilt encoded data slice, and the memory group identifier to
produce ranked scoring information. The processing module
identifies the corresponding memory device associated with a
highest score of the ranked scoring information.
For each rebuilt encoded data slice, the method continues at step
438 where the processing module stores the rebuilt encoded data
slice in the corresponding identified memory device. For example,
the processing module sends the encoded data slice to the
identified corresponding memory device for each rebuilt encoded
data slice.
FIG. 42A is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) that includes the distributed
storage and task (DST) processing unit 16 of FIG. 1, the network 24
of FIG. 1, and a DST execution (EX) unit pool 440. The DST
processing unit 16 includes a decentralized agreement module 442
and the DST client module 34 of FIG. 1. The decentralized agreement
module 442 may be implemented utilizing the decentralized agreement
module 350 of FIG. 40A. The DST execution unit pool 440 includes a
plurality of DST execution units 1-N, where the plurality includes
a subset of DST execution units 1-n such that n<N. For example,
the subset of DST execution units includes an information dispersal
algorithm (IDA) width number n of storage units (e.g., 16) of a
total number of N storage units (e.g., N=20), where a decode
threshold number of the IDA is 10, and where the decode threshold
number of encoded data slices is required to recover data.
The DSN functions to access data stored as a plurality of sets of
encoded data slices in the DST execution unit pool, where a
decentralized agreement function is utilized to select DST
execution units of the DST execution unit pool to facilitate the
access. The data access includes storing the data and retrieving
the data.
In an example of operation of the storing of the data utilizing the
decentralized agreement function, the DST client module 34 receives
a data access request 444 that includes data for storage. Having
received the data access request 444, the DST client module 34
determines a DSN address associated with the data access request.
Having determined the DSN address, the DST client module 34
identifies a storage pool of DST execution units for storage of the
data. The identifying includes at least one of utilizing a
decentralized agreement function based on the DSN address,
performing a lookup based on the DSN address, and receiving
identity of the storage pool.
Having identified the storage pool, the DST client module 34
determines a resource level selection approach. The approach may
include at least one of storage units of the storage pool and
storage units by site. The determining may be based on one or more
of performing a lookup, receiving via the data access requests, and
interpreting a DST execution unit availability indicator. For
example, the DST client module 34 selects storage units from the
storage unit pool.
Having determined the resource level selection approach, the DST
client module 34 obtains ranked scoring information 448 for DST
execution units of the storage pool in accordance with the resource
level approach. For example, the DST client module 34 issues a rank
scoring information request 446 to the decentralized agreement
module 442 for each storage unit of the storage pool using location
weights of each storage unit, a storage pool identifier, and the
DSN address. The DST client module 34 receives the ranked scoring
information 448 in response.
Having received the ranked scoring information 448, the DST client
module 34 selects an IDA width number of DST execution units of the
storage pool based on the ranked scoring information 448 and the
resource level selection approach. For example, the DST client
module 34 selects an IDA width number of storage units associated
with a 16 highest ranked scores when the IDA width is 16 and the
approach is selection by storage pool. As another example, the DST
client module 34 selects a write threshold number of storage units
associated with highest scores.
Having selected the IDA width number of DST execution units, the
DST client module 34 issues resource access requests 450 that
includes write slice requests to the selected IDA width number of
DST execution units. For example, the DST client module 34
dispersed storage error encodes the data to produce a plurality of
sets of encoded data slices, generates a set of 16 write slice
requests that includes the plurality of sets of encoded data
slices, and sends, via the network 24, the set of 16 write slice
requests to the selected DST execution units of the DST execution
unit pool.
The DST client module 34 receives resource access responses 452
with regards to storage of the plurality of sets of encoded data
slices. For example, the resource access responses 452 includes one
or more write slice responses indicating status of writing encoded
data slices. When receiving an indication of a write failure, the
DST client module 34 selects another DST execution unit based on
the ranked scoring information. For example, the DST client module
34 selects a next highest ranked DST execution unit of the DST
execution unit pool. When selecting another DST execution unit, the
DST client module 34 sends, via the network 24, a corresponding
write slice request to the selected other DST execution unit. The
DST client module 34 issues a data access response 454 to a
requesting entity based on received resource access responses 452
(e.g., success or failure of the writing).
In an example of operation of the retrieving of the data utilizing
the decentralized agreement function, the DST client module 34
receives a data access request 444 that includes a retrieval
request for the data. The DST client module 34 determines the DSN
address associated with the data access request and identifies the
storage pool of the DST execution units for storage of the data.
The DST client module 34 determines the resource level selection
approach and obtains the rank scoring information 448 for the DST
execution units of the storage pool in accordance with the resource
level selection approach.
Having obtained the rank scoring information 448, the DST client
module 34 selects a decode threshold number plus m number of DST
execution units of the DST execution unit pool based on the ranked
scoring information 448 and the resource level selection approach
(e.g., select 10+2 more storage units with highest ranked scores
when the decode threshold is 10 and the approach is selection by
storage pool). Having selected the DST execution units, the DST
client module 34 issues resource access requests 450 to the
selected DST execution units, where the resource access requests
450 includes read slice requests. For example, the DST client
module 34 generates a set of read slice requests, sends, via the
network 24, the read slice requests to the selected DST execution
units, and receives resource access responses 452 that includes
received encoded data slices.
Having received encoded data slices, the DST client module 34
outputs another data access response 454 to the requesting entity
based on the received encoded data slices of the resource access
responses 452. For example, the DST client module 34 decodes the
received encoded data slices to produce recovered data and issues
the data access response 454 to include the recovered data.
FIG. 42B is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) that includes the distribute
storage and task (DST) processing unit 16 of FIG. 42A, the network
24 of FIG. 1, and a DST execution (EX) unit pool 458. The DST
execution unit pool 458 includes a plurality of DST execution units
1-20, where at least one DST execution unit is implemented at each
of at least two sites. For example, five DST execution units are
implemented at each of four sites when the number of DST execution
units is 20. Each DST execution unit may be implemented utilizing
the DST execution unit 36 of FIG. 1.
The DSN functions to access data stored as a plurality of sets of
encoded data slices in the DST execution unit pool 458, where a
decentralized agreement function is utilized to select DST
execution units of the DST execution unit pool 458 to facilitate
the access. The data access includes storing the data and
retrieving the data. In an example of operation, the DST processing
unit 16 receives a data access request 460, selects DST execution
units of the DST execution unit pool 458, issues resource access
requests 466, via the network 24, to the selected DST execution
units, receives resource access responses 468, generates a data
access response 470 based on the received resource access responses
468, and outputs the data access response 470 to a requesting
entity. The selecting of the DST execution units further includes
selecting DST execution units based on DST execution unit-to-site
implementation.
In another example of operation, when storing the data, the DST
processing unit 16 utilizes the decentralized agreement function to
select an information dispersal algorithm (IDA) width number of DST
execution units in total. Alternatively, the DST processing unit 16
selects a write threshold number of DST execution units. The
selecting includes determining a number of DST execution units for
each site based on a number of sites and the IDA width number. For
example, the DST client module 34 divides the IDA width number of
16 by 4 sites to indicate that four DST execution units per site
shall be selected. Having determined the number of DST execution
units for selection by site, the DST client module 34 utilizes the
decentralized agreement function (e.g., issues a ranked scoring
information request 462 to the decentralized agreement module 442)
to produce ranked scoring information 464 for each subset of DST
execution units at each site to identify a highest ranked four of
five DST execution units as the selected DST execution units. The
DST client module 34 utilizes the selected DST execution units for
storage of the data.
When retrieving the data, the DST processing unit 16 utilizes the
decentralized agreement function to select a read threshold number
of DST execution units in total (e.g., decode threshold plus two).
The read threshold number is greater than or equal to a decode
threshold number and less than or equal to the IDA width number.
The selecting includes determining the number of DST execution
units for each site based on the number of sites and the IDA width
number. For example, the DST client module 34 divides the IDA width
number of 16 by 4 sites to indicate that four DST execution units
per site shall be considered for final selection. Having determined
the number of DST execution units for consideration by site, the
DST client module 34 utilizes the decentralized agreement function
to produce ranked scoring information 464 for each subset of DST
execution units at each site to identify a highest ranked four of
five DST execution units as candidate for retrieval DST execution
units.
Having identified candidate DST execution units, the DST client
module 34 determines a number of DST execution units for each site
to be selected based on the read threshold number and the number of
sites. For example, the DST client module 34 divides the read
threshold number of 12 by 4 sites to indicate that three DST
execution units per site shall be selected in the final selection.
The DST client module 34 selects three DST execution units
associated with highest ranked scoring information of the
previously identified highest ranked four of five DST execution
units per site. The DST client module 34 utilizes the selected DST
execution units for the retrieval of the data.
FIG. 42C is a flowchart illustrating an example of selecting
storage resources. The method begins or continues, when storing
data, at step 474 where a processing module (e.g., of a distributed
storage and task (DST) client module) receives data for storage.
The receiving may further include generating a source name and
updating a directory to associate the source name with a data
identifier of the data. The method continues at step 476 where the
processing module determines a dispersed storage network (DSN)
address based on the data access request. For example, the
processing module performs a lookup based on the DSN addresses.
The method continues at step 478 where the processing module
identifies a storage pool of storage units for storage of the data.
For example, the processing module performs a decentralized
agreement function based on the DSN address to select the storage
pool from a plurality of storage pools. The method continues at
step 480 where the processing module determines a resource level
selection approach. The determining may be based on one or more of
a predetermination, a request, and interpreting storage unit
availability.
The method continues at step 482 where the processing module
obtains ranked scoring information for storage units of the storage
pool in accordance with the resource level selection approach. For
example, the processing module calculates a score for each storage
unit using the decentralized agreement function based on a location
weight of the storage unit, a storage pool identifier, and the DSN
address.
The method continues at step 484 where the processing module
selects an information dispersal algorithm (IDA) width number of
storage units based on the ranked scoring information and the
resource level selection approach. For example, for a storage pool
approach, the processing module selects storage units associated
with a highest score on a per-site basis, where substantially
identical number of storage units are selected for each site
associated with storage pool.
The method continues at step 486 where the processing module issues
write slice requests to the selected storage units. For example,
the processing module dispersed storage error encodes the data,
generates read slice requests, and sends the write slice requests
to the selected storage units. Upon a write failure, the processing
module issues another write slice request to another storage unit
(e.g., associated with a next highest score).
The method begins or continues, when retrieving the data, at step
490 where the processing module receives a retrieve request for the
data. The method continues at step 492 where the processing module
determines the DSN address based on the retrieval request. The
method continues at step 494 where the processing module identifies
a storage pool of storage units for storage of the data. The method
continues at step 496 where the processing module determines the
resource level selection approach. The method continues at step 498
where the processing module obtains the ranked scoring information
for the storage units of the storage pool in accordance with the
resource level selection approach.
The method continues at step 500 where the processing module
selects a read threshold number of storage units based on the
ranked scoring information and the resource level selection
approach. For example, the processing module selects a read
threshold number associated with highest scores, where a number of
selected storage units per site is substantially the same. The
method continues at step 502 of the processing module recovers the
data from the selected storage units. For example, the processing
module generates a set of read slice requests, sends the set of
read slice requests to the selected storage units, receives encoded
data slices, dispersed storage error decodes the received encoded
data slices to produce recovered data, and outputs the data access
response to a requesting entity that includes the recovered
data.
FIG. 43A is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) that includes the distributed
storage and task (DST) processing unit 16 of FIG. 1, the network 24
of FIG. 1, a DST execution (EX) unit legacy pool 510, and a DST
execution unit non-legacy pool 512. The DST processing unit 16
includes a decentralized agreement module 514 and the DST client
module 34 of FIG. 1. The decentralized agreement module 514 be
implemented utilizing the decentralized agreement module 350 of
FIG. 40A. The DST execution unit legacy pool 510 includes a
plurality of DST execution unit generations 1-G. Each DST execution
unit generation includes a set of DST execution units 1-n. Each DST
execution unit may be implemented utilizing the DST execution unit
36 of FIG. 1. The DST execution unit non-legacy pool 512 includes a
plurality of DST execution unit pools 1-P. Each DST execution unit
pool includes a set of DST execution units 1-n.
The DSN functions to access data stored as a plurality of sets of
encoded data slices in at least one set of DST execution units. The
accessing of the data includes selecting the set of DST execution
units using one or more of a decentralized agreement function and a
DSN addressing mapping. As a specific example, the DST processing
unit 16 receives a data access request 516; selects one of the DST
execution unit legacy pool 510 and a particular set of DST
execution units of DST execution unit non-legacy pool 512 using the
decentralized agreement function, where the DST processing unit
utilizes the DSN addressing mapping to further select a DST
execution unit generation when selecting the DST execution unit
legacy pool; accesses, issuing resource access requests 522 and
receiving resource access responses 524, at least one of the
particular set of DST execution units of the DST execution unit
non-legacy pool and the further selected DST execution unit
generation; and issues a data access response 526 based on the
received resource access responses 524.
In an example of operation of the accessing of the data, the DST
client module 34 obtains a DSN address associated with the data
access request 516 and obtains ranked scoring information 520 or
the DST execution unit legacy pool and one or more DST execution
unit pools of the DST execution unit non-legacy pool. For example,
the DST client module 34 issues a ranked scoring information
request 518 to the decentralized agreement module 514 utilizing
location weights associated with each DST execution unit legacy
pool and the DST execution unit non-legacy pool, a storage pool
identifier, and the DSN address; and receives the ranked scoring
information 520. For instance, a location weight of 800 is
associated with the DST execution unit legacy pool, a location
weight of 100 is associated with DST execution unit pool 1, etc.,
and a location weight of 300 is associated with DST execution unit
pool P.
Having obtained the ranked scoring information 520, the DST client
module 34 selects one of the DST execution unit legacy pool and one
of the one or more DST execution unit pools of the DST execution
unit non-legacy pool based on the ranked scoring information 520.
For example, the DST client module 34 performs the selection by
identifying a pool associated with a highest score.
When selecting the DST execution unit legacy pool, the DST client
module 34 accesses, in accordance with the data access request, a
DST execution unit generation that corresponds to the DSN address
(e.g., identify the DST execution unit generation based on a
generation field of the DSN address). The accessing includes
issuing resource access requests 522 (e.g., write slice requests,
read slice request, delete slice requests, list slice requests,
etc.). The accessing further includes receiving resource access
responses 524 (e.g., write slice responses, read slice responses,
delete slice responses, list slice responses, etc.).
When selecting the one of the one or more DST execution unit pools,
the DST client module 34 accesses, in accordance with the data
access requests, the selected DST execution unit pool. The
accessing includes issuing the resource access requests 522 and
receiving the resource access responses 524. Having received the
resource access responses 524, the DST client module 34 issues the
data access response 526 to a requesting entity based on the
received resource access responses 524.
FIG. 43B is a flowchart illustrating another example of selecting
storage resources slices. The method begins or continues at step
530 where a processing module (e.g., of a distributed storage and
task (DST) client module) obtains a dispersed storage network (DSN)
address associated with a data access request from a requesting
entity. The obtaining includes at least one of generating,
performing a lookup, and receiving. The method continues at step
532 where the processing module obtains ranked scoring information
for a legacy storage unit pool and one or more non-legacy storage
unit pools based on the DSN address. As a specific example, the
processing module utilizes a decentralized agreement function to
generate a score of the ranked scoring information for each storage
pool using the location weights of the storage pool, a storage pool
identifier, and the DSN address.
The method continues at step 534 where the processing module
selects one of the legacy storage unit pool and the one or more
non-legacy storage pools based on the ranked scoring information to
produce a selected storage unit pool. For example, the processing
module identifies a pool associated with a highest score and
selects the pool associated with the highest score as the selected
storage unit pool.
When the selected storage unit pool includes the legacy storage
unit pool, the method continues at step 536 where the processing
module accesses resources of the legacy storage unit pool in
accordance with the data access request and based on the DSN
address. For example, the processing module selects a storage unit
generation based on a generation field of the DSN address, issues
write slice requests to the selected storage unit generation for a
store data access request or issues read slice requests to the
selected storage unit generation for a retrieve data access
request, and receives responses.
When the selected storage unit pool includes one non-legacy storage
unit pool, the method continues at step 538 where the processing
module accesses resources of the non-legacy storage unit pool in
accordance with the data access request. For example, the
processing module issues write slice requests to storage units of
the selected storage unit pool for the store data request or issues
read slice requests to the storage units of the selected storage
unit pool for the retrieve data access request, and receives the
responses. When receiving access responses, the processing module
generates a data access response based on the received access
responses and outputs the data access response to the requesting
entity.
FIG. 44A is a schematic block diagram of another embodiment of a
distributed storage and task (DST) execution (EX) unit 540 that
includes the processing module 84 of FIG. 3 and the memory device
88 of FIG. 3. The DST execution unit 540 functions to provide
access to slices 542 stored in the memory device 88. The accessing
includes storing and retrieving.
An example of operation of the storing, the processing module 84
receives a write slice requests that includes an encoded data slice
for storage and a slice name of the encoded data slice. For
example, the processing module 84 receives an encoded data slice
with a slice name of A-1. The processing module 84 obtains a bucket
file for storage of the encoded data slice. The processing module
84 organizes a portion of the memory device 88 to provide a
plurality of bucket files 1-B, where each bucket file may be
utilized to store one or more encoded data slices. Each bucket file
may be fixed or variable in size. Each bucket file may be unique in
size or substantially the same. The obtaining of the bucket file
includes selecting an existing bucket file, where the existing
bucket file includes available space and generating a new bucket
file when a size of the received encoded data slices greater than
available space of the existing bucket file. For example, the
processing module 84 selects bucket file 1 for storage of the
encoded data slice A-1.
Having obtained the bucket file, the processing module 84 selects
an offset within the selected bucket file, where sufficient space
exists within the bucket file starting at the offset for the
encoded data slice, a start delimiter, and an end a delimiter.
Alternatively, the offset may further include a memory device
identifier when a plurality of memory devices 88 are utilized. The
selecting may include accessing an offset list 546 from the memory
device 88, where the offset list includes associations of slice
names, bucket file identifiers, and offsets. For example, the
processing module 84 selects an offset of 300 based on available
storage space for encoded data slice A-1.
Having selected the offset, the processing module 84 updates the
offset list 546 to associate the slice name, the selected bucket
file, and the selected offset. For example, the processing module
84 associates slice name A-1 with bucket file 1 at an offset of
300.
Having updated the offset list 546, the processing module 84
generates the start and end delimiters for the encoded data slice.
As a specific example, the processing module 84 performs a
deterministic function on a combination of a random parameter
hundred and 44, the bucket file identifier, and a start or and
slice indicator. The deterministic function includes at least one
of a hashing function, a hash-based message authentication code
function, a mask generating function, and a sponge function. The
random parameter 544 may be associated with at least one of DST
execution unit and each bucket file. As a specific example, the
processing module 84 generates the random parameter 544 when a new
bucket file is created using at least one of a cryptographic secure
random number generator, a pseudo random number generator, and
entropy source generator, a key generator, and a random seed. The
processing module 84 stores the random parameter 544 in the memory
device 88 and may further store an association indicator indicating
whether the rent parameters associated with the DST execution unit
or a particular bucket file.
Having generated the start and end delimiters, the processing
module 84 issues a write slice rejection response to a requesting
entity when detecting either of the start and end delimiters within
the encoded data slice. When not detecting either of the start and
end delimiters within the encoded data slice, the processing module
84 stores, starting at the offset within the selected bucket list,
the start delimiter, the encoded data slice, and the end
delimiter.
An example of operation of the retrieving, the processing module 84
receives a read slice requests that includes the slice name. The
processing module 84 identifies the bucket file and offset for
retrieval of the encoded data slice by accessing the offset list
based on a slice name. Having identified the bucket file an offset,
the processing module 84 accesses the bucket file within the memory
88 using the offset to identify the start delimiter associated with
the encoded data slice. Having identified the start delimiter, the
processing module 84 extracts encoded data slice from the bucket
file immediately after the start delimiter and ending when
identifying the end delimiter. Having extracted the encoded data
slice, the processing module 84 sends the encoded data slice to a
requesting entity.
FIG. 44B is a flowchart illustrating an example of de-marking
encoded data slices. The method begins or continues, when storing
an encoded data slice, at step 550 where a processing module (e.g.,
of a distributed storage and task (DST) client module) receives a
write slice request that includes the encoded data slice and a
slice name. The method continues at step 552 where the processing
module obtains a bucket file for storage of the encoded data slice.
For example, the processing module selects an existing bucket file
associated with sufficient storage space. As another example, the
processing module generates a new bucket file when not locating an
existing bucket file with sufficient space.
The method continues at step 554 where the processing module
selects an offset within the bucket file for storage of the encoded
data slice. For example, the processing module identifies a space
between two existing offsets associated with sufficient space for
storage of the encoded data slice and identifies the offset of the
start of the identified space. Alternatively, the offset may
further include identification of a memory device of the plurality
of memory devices.
The method continues at step 556 where the processing module
updates an offset list to associate the slice name, the selected
bucket file, and the selected offset. For example, the processing
module recovers the offset list, updates the offset list to produce
an updated offset list, and stores the updated offset list.
The method continues at step 558 where the processing module
generates start and end delimiters for the encoded data slice based
on the bucket file. For example, the processing module performs a
deterministic function on a combination of one or more of a random
parameter, a bucket file identifier, and a start or and slice
indicator. The method continues at step 560 where the processing
module issues a write slice rejection response to a requesting
entity when detecting either of the start and end delimiters within
the encoded data slice. The method continues at step 562 where the
processing module stores, starting at the offset within the
selected bucket file, the start delimiter, the encoded data slice,
and the end delimiter when not detecting either of the start and
end delimiters within the encoded data slice.
FIGS. 45A-45E are a schematic block diagram of another embodiment
of a dispersed storage network (DSN) that includes the distributed
storage and task (DST) processing unit 16 of FIG. 1, the
distributed storage and task network (DSTN) managing unit 18 of
FIG. 1, the network 24 of FIG. 1, and storage sets 1 and 2. The DST
processing unit 16 includes a decentralized agreement module 570
and the DST client module 34 of FIG. 1. The decentralized agreement
module 570 may be implemented utilizing the decentralized agreement
module 350 of FIG. 40A. The DSTN managing unit 18 includes the
decentralized agreement module 570 and the DST client module 34 of
FIG. 1. Each storage set includes a set of n DST execution (EX)
units. Each DST execution unit includes the decentralized agreement
module 570, the DST client module 34 of FIG. 1, and the memory 88
of FIG. 3. Each DST execution unit may be implemented utilizing the
DST execution unit 36 of FIG. 1. Hereafter, each DST execution unit
may be interchangeably referred to as a storage unit, a storage set
may be interchangeably referred to as a set of storage units, and
the storage sets 1 and 2 may be interchangeably referred to as a
DSN memory. The DSN functions to access data while migrating
storage of the data, where the DST processing unit 16 dispersed
storage error encodes the data to produce a plurality of sets of
encoded data slices 574 and stores the plurality of sets of encoded
data slices 574 in at least one storage set to store the data.
FIG. 45A illustrates steps of an example of operation of the
accessing of the data while migrating the storage of the data where
the DSTN managing unit 18 issues, via the network 24, pending
weights 572 to the storage units 1-n of the storage sets 1 and 2.
The pending weights 572 include future weighting factors for one or
more storage resources of the DSN memory. Examples of future
weighting factors includes a future weighting factor for a memory
to be decommissioned, a future weighting factor for a memory to be
commissioned, a future weighting factor for a storage unit to be
decommissioned, the future weighting factor for a storage unit to
be commissioned, a future weighting factor for a storage set to be
decommissioned, and a future weighting factor for a storage set to
be commissioned.
The issuing of the pending weights 572 includes one or more of
detecting weighting factor changes, generating the pending weights
572 based on the detected weighting factor changes, identifying
effected storage units of the storage sets, and sending, via the
network 24, the pending weights 572 to the effected storage units
of the storage sets. The identifying of the effected storage units
includes identifying at least one DSN address range associated with
the effected storage units, where performing a distributed
agreement protocol function on the DSN address range utilizing
either of the pending weights 572 and current weights (e.g., before
upcoming changes when the pending weights are made current)
produces ranked scoring information that identifies highest-ranking
storage resources to produce the effected storage units. For
instance, the DST client module 34 of the DSTN managing unit 18
utilizes the decentralized agreement module 570 to identify storage
units of the storage set 1 and storage units of the storage set 2
as effected by the pending weights 572.
The plurality of storage units of the DSN receives the pending
weights 572 as updated properties of the DSN memory, where the
updated properties of the DSN memory requires storage migration
within the DSN memory. For example, the storage migration is
required to select and migrate slices 574 as transfer slices 576
from storage units of the storage set 1 to the storage units of the
storage set 2 when the future weighting factors of the storage
units of the storage set 1 are lowered and the future weighting
factors of the storage units of the storage set 2 are raised.
Having received the updated properties of the DSN memory (e.g.,
including pending weights 572), a first storage unit and a second
storage unit of the plurality of storage units establish a
migration pairing based on the updated properties of the DSN
memory. Alternatively, the DST client module 34 of the DSTN
managing unit 18 establishes the migration pairing. The
establishing of the migration pairing may include performing, by
the first storage unit, a scoring function (e.g., the distributed
agreement protocol function by the decentralized agreement module
570) using one or more properties of DSN access information (e.g.,
a DSN address range associated with a given storage set) and one or
more properties of non-updated properties of the DSN memory (e.g.,
current weighting factors of DSN memory resources) to identify a
range of DSN addresses affiliated with the first storage unit,
performing, by the second storage unit, the scoring function using
the one or more properties of DSN access information and the one or
more properties of non-updated properties of the DSN memory to
identify the range of DSN addresses affiliated with the first
storage unit, performing, by the first storage unit, an updated
scoring function using the one or more properties of DSN access
information and one or more properties of the updated properties of
the DSN memory (e.g., the pending weights 572) to identify a range
of DSN addresses affiliated with the second storage unit (e.g.,
where changes), performing, by the second storage unit, the updated
scoring function using the one or more properties of DSN access
information and the one or more properties of the updated
properties of the DSN memory to identify the range of DSN addresses
affiliated with the second storage unit, and establishing, by the
first and second storage units, the migration pairing based on the
range of DSN addresses being affiliated with the first storage unit
based on the non-updated properties of the DSN memory and the range
of DSN addresses being affiliated with the second storage unit
based on the updated properties of the DSN memory.
As a specific example of the establishing of the migration pairing,
the DST execution unit 1-2 and the DST execution unit 2-2 identify
a DSN address range affiliated with the DST execution unit 1-2
(e.g., associated with slices 574 currently stored within the
memory 88 of the DST execution unit 1-2) effected by the pending
weights 572, where encoded data slices associated with the
identified DSN address range are to be migrated as the transfer
slices 576 from the DST execution unit 1-2 to the DST execution
unit 2-2. With the migration pairing established, the first and
second storage units establish, between the first and second
storage units, a storage migration mechanism for migrating storage
of data between the first and second storage units based on the
updated properties of the DSN memory. Alternatively, the DSTN
managing unit 18 establishes the storage migration mechanism.
The establishing of the storage migration mechanism may include one
or more of identifying an address range to migrate, identifying
stored data having an address within the address range to migrate,
establishing a data migration list that includes the identified
stored data, establishing a data migration pattern for migrating
the identified stored data between the first and second storage
units, and updating the data migration list as the identified
stored data is migrated between the first and second storage units.
For example, the DST execution unit 1-2 identifies the DSN address
range associated with stored encoded data slices 574, where the
stored encoded data slices 574 are associated with the DST
execution unit 1-2 when utilizing the non-updated properties of the
DSN memory (e.g., current weighting factors), establishes the data
migration list to include slice names of the stored encoded data
slices 574 associated with the DSN address range, establishes the
data migration pattern that includes sending, via the network 24,
the identified stored encoded data slices 574 as transfer slices
576 to the DST execution unit 2-2, and facilitates the migration of
the transfer slices 576, and updates the data migration list as the
transfer slices 576 are confirmed to be received and stored in the
memory 88 of the DST execution unit 2-2.
The establishing of the storage migration mechanism may further
include determining, based on the non-updated properties of the DSN
memory (e.g., current weighting factors), a source storage unit of
the first and second storage units, determining, based on the
updated properties of the DSN memory, a destination storage unit of
the first and second storage units, and sending the identified
stored data from the source storage unit to the destination storage
unit. For example, the pairing of the DST execution units 1-2 and
2-2 determines that the DST execution unit 1-2 is the source
storage unit, determines that the DST execution unit 2-2 is the
destination storage unit, and DST execution unit 1-2 sends the
identified encoded data slices of the identified stored data as
transfer slices 576 to the DST execution unit 2-2 for storage.
FIG. 45B illustrates further steps of the example of operation of
the accessing of the data while migrating the storage of the data,
where encoded data slices associated with the identified DSN
address range are migrated from the DST execution unit 1-2 to the
DST execution unit 2-2. For example, the DST execution unit 1-2
identifies encoded data slices A-1 through A-N of a transfer range
1 of the DSN address range and excludes encoded data slices B-1
through B-N from the store data migration (e.g., not associated
with the identified DSN address range), where the memory 88 of the
DST execution unit 1-2 stores the stored encoded data slices
574.
While migrating the storage of the data between the first and
second storage units in accordance with the storage migration
mechanism, the first or second storage unit receives a data access
request (e.g., new data object write request, new revision data
object write request, read request) regarding the data effected by
the migrating the storage of data between the first and second
storage units. The receiving the data access request may include
receiving the data access request by the first storage unit when
the data access request was created in accordance with the updated
properties of DSN memory and receiving the data access request by
the second storage unit when the data access request was created in
accordance with non-updated properties of DSN memory.
For example, with the migrating of the storage of the data
initiated, where at a given point in time a portion of the encoded
data slices associated with the identified DSN address range have
been successfully migrated and a remaining portion of the encoded
data slices associated with the identified DSN address range have
not yet been successfully migrated (e.g., encoded data slices A-1
and A-2 have been transferred from the DST execution unit 1-2 to
the DST execution unit 2-2), a requesting entity (e.g., the DST
processing unit 16) attempts to access the DSN memory to access one
or more of the encoded data slices associated with the identified
DSN address range. As a specific example, the DST client module 34
of the DST processing unit 16 utilizes the decentralized agreement
module 570 to perform the distributed agreement protocol function
on a DSN address associated with a desired data object of access
using the non-updated DSN properties (e.g., current weighting
factors of the storage units) to identify the DST execution unit
1-2 as affiliated with the encoded data slices A-1 through A-N and
sends, via the network 24, slice requests to the DST execution unit
1-2 with regards to accessing at least some of the encoded data
slices A-1 through N-N. For instance, the DST processing unit 16
sends slice requests A-1 and A-2 to the DST execution unit 1-2
based on non-updated DSN properties (e.g., current weighting
factors). The example of operation is continued as discussed with
reference to FIG. 45C.
FIG. 45C illustrates further steps of the example of operation of
the accessing of the data while migrating the storage of the data
where the first storage unit or the second storage unit determines
status of the migrating storage of data between the first and
second storage units. For example, the DST execution units 1-2 and
2-2 determine that the status of the migrating storage of the data
indicates that the encoded data slices A-1 and A-2 have been
successfully transferred and encoded data slices A-3 through A-N
are pending transfer. The determining of the status may be
facilitated in accordance with a status determining approach based
on a type of the data access request (e.g., read request, new write
request, revision write request). When the type of the data access
request is the read request, the determining the status of the
migrating storage of the data includes accessing the migration list
of data being migrated between the first and second storage units,
determining whether a data object of the read request has been
migrated based on the migration list, when the data object has been
migrated, indicating the status as migrated to destination, and
when the data object has not been migrated, indicating the status
as not migrated to destination.
When the type of the data access request is the new write request,
the determining the status of the migrating storage of the data
includes, when the first and second storage units possess the
updated properties of the DSN memory, setting the status for the
new write request as write to destination (e.g., indicate that the
DST execution unit 2-2 is to execute the new write request). When
the type of the data access request is the revision write request
for a revised data object, the determining the status of the
migrating storage of the data includes accessing the migration list
of data being migrated between the first and second storage units,
determining whether a predetermined number (e.g., all or almost
all) of data objects on the migration list have been migrated to a
destination, when the predetermined number of data objects have
been migrated, indicating the status as migrated to destination,
and when the predetermined number of data objects have not been
migrated, indicating the status as not migrated to destination.
Having determined the status, the first storage unit or the second
storage unit determines which of the first and second storage units
is to process the data access request based on the status to
produce a determined storage unit. The determining may be based on
the type of the data access request. When the type of the data
access request is the read request, the determining the determined
storage unit includes determining that the first storage unit is
the determined storage unit when the read request was created based
on non-updated properties of the DSN memory and the status is not
migrated to destination, determining that the second storage unit
is the determined storage unit when the read request was created
based on the non-updated properties of the DSN memory and the
status is migrated to destination (e.g., the DST execution unit 2-2
is identified to process the data access request when the data
access request as the read request and the encoded data slices A-1
and A-2 has been successfully migrated to the DST execution unit
2-2), determining that the first storage unit is the determined
storage unit when the read request was created based on updated
properties of the DSN memory and the status is not migrated to
destination, and determining that the second storage unit is the
determined storage unit when the read request was created based on
the updated properties of the DSN memory and the status is migrated
to destination.
When the type of the data access request is the new write request,
the determining the determined storage unit includes when the
status indicates write to destination, performing an updated
scoring function using one or more properties of the new write
request and one or more properties of the updated properties of the
DSN memory to identify the second storage unit as the determined
storage unit. When the type of the data access request is the
revision write request for the revised data object, the determining
the determined storage unit includes when the status indicates
migrated to destination, identifying the second storage unit as the
destination and as the determined storage unit, and when the status
indicates not migrated to destination, identifying the first
storage unit as a source and as the determined storage unit.
Having determined the determined storage unit, the determined
storage unit processes the data access request. The processing may
be based on the type of the data access request. When the type of
the data access request is the read request, the processing the
data access request includes the determined storage unit processes
the read request. The processing may include forwarding, by another
storage unit, the read request to the determined storage unit. For
example, the DST execution unit 1-2 forwards, via the network 24,
the slice request A-1, A-2 as a forward slice request A-1, A-2 to
the DST execution unit 2-2 when the DST execution unit 2-2 is the
determined storage unit for the read request and the DST execution
unit 2-2 issues, via the network 24, a slice response A-1, A-2 that
includes the encoded data slices A-1 and A-2 to the DST processing
unit 16.
When the type of the data access request is the new write request,
the processing the data access includes storing the data object by
the second storage unit and updating the migration list to include
that the data object has been migrated to the destination. The
processing may include forwarding the new write request to the
determined storage unit. For example, the DST execution unit 1-2
forwards the write request (e.g., write slice request) to the DST
execution unit 2-2, the DST execution unit 2-2 stores new encoded
data slices of the new data object in the memory 88, and issues a
write slice response A-1, A-2 to the DST processing unit 16
indicating status of the new write request.
When the type of the data access request is the revision write
request for the revised data object, the processing the data access
includes, when the status indicates migrated to destination,
storing the revised data object by the second storage unit, and
updating the migration list to include that the revised data object
has been migrated to the destination, and, when the status
indicates not migrated to the destination, storing the revised data
object by the first storage unit, and updating the migration list
to include that the revised data object has not been migrated to
the destination. For example, when the status indicates migrated to
destination, the DST execution unit 1-2 forwards the revision write
request to the DST execution unit 2-2. As another example, when the
status indicates that migrated to the destination, the DST
execution unit 1-2 stores the revision encoded data slices in the
memory 88 of the DST execution unit 1-2 and updates the migration
list to include that the device data object has not been migrated
to the destination (e.g., default).
FIG. 45D illustrates further steps of the example of operation of
the accessing of the data while migrating the storage of the data
where the requesting entity of the data access utilizes the updated
DSN properties (e.g., the pending weights) to identify the DST
execution unit for the data access request and sends a
corresponding slice access request to the identified DST execution
unit. For example, the DST processing unit 16 issues, via the
network 24, a slice request A-3, A-4 to the DST execution unit 2-2
when the corresponding encoded data slices A-3, A-4 have not yet
been migrated from the DST execution unit 1-2 to the DST execution
unit 2-2.
Having received the data access request, the first storage unit or
the second storage unit determines the status of the migrating the
storage of the data between the first and second storage units. For
instance, the first and second storage units determined that the
status indicates that only encoded data slices A-1 and A-2 have
been successfully transferred to the DST execution unit 2-2. Having
determined the status, the first or second storage units determine
which of the first and second storage units is to process the data
access request based on the status to produce the determined
storage unit. For example, the DST execution units 1-2 and 2-2
determine that the DST execution unit 1-2 shall process the data
access request as the determined storage unit when the encoded data
slices A-3 and A-4 of the data access request have not yet been
transferred.
Having identified the determined storage unit, the determined
storage unit processes the data access request. For example, the
DST execution unit 2-2 forwards, via the network 24, the slice
request A-3, A-4 to the DST execution unit 1-2, the DST execution
unit 1-2 processes the data access request to produce a slice
response A-3, A-4, and sends, via the network 24, the slice
response A-3, A-4 to the DST processing unit 16.
FIG. 45E illustrates further steps of the example of operation of
the accessing of the data while migrating the storage of the data
where the determined storage unit (e.g., DST execution unit 2-2)
issues, via the network 24, a transfer complete message (e.g.,
transfer complete A-1 through A-N) to the DSTN managing unit 18
indicating that the identified encoded data slices of the
identified DSN address range for migration have been successfully
transferred from the DST execution unit 1-2 to the DST execution
unit 2-2. Having received the transfer complete message, the DSTN
managing unit 18 issues, via the network 24, confirmed weights 578
to one or more entities of the DSN. The confirmed weights 578
include the updated DSN parameters (e.g., updated weighting factors
associated with the affected storage units of the migration of the
stored data). For example, the DSTN managing unit 18, sends, the
confirmed weights 578 to the DST processing unit 16 for utilization
in accessing the DSN memory.
FIG. 45F is a flowchart illustrating an example of accessing data
while migrating storage of the data. In particular, a method is
presented for use in conjunction with one or more functions and
features described in conjunction with FIGS. 1-39, 45A-E, and also
FIG. 45F. The method begins or continues at step 580 where a
plurality of storage units, that includes one or more processing
module of one or more computing devices of one or more computing
devices of a dispersed storage network (DSN), receives updated
properties of DSN memory, where the DSN memory includes the
plurality of storage units and where the updated properties of the
DSN memory requires storage migration within the DSN memory.
The method continues at step 582 where a first storage unit and a
second storage unit of the plurality of storage units establish a
migration pairing based on the updated properties of the DSN
memory. The establishing the migration pairing may include
performing, by the first storage unit, a scoring function using one
or more properties of DSN access information and one or more
properties of non-updated properties of the DSN memory to identify
a range of DSN addresses affiliated with the first storage unit,
performing, by the second storage unit, the scoring function using
the one or more properties of DSN access information and the one or
more properties of non-updated properties of the DSN memory to
identify the range of DSN addresses affiliated with the first
storage unit, performing, by the first storage unit, an updated
scoring function using the one or more properties of DSN access
information and one or more properties of the updated properties of
the DSN memory to identify a range of DSN addresses affiliated with
the second storage unit, performing, by the second storage unit,
the updated scoring function using the one or more properties of
DSN access information and the one or more properties of the
updated properties of the DSN memory to identify the range of DSN
addresses affiliated with the second storage unit, and
establishing, by the first and second storage units, the migration
pairing based on the range of DSN addresses being affiliated with
the first storage unit based on the non-updated properties of the
DSN memory and the range of DSN addresses being affiliated with the
second storage unit based on the updated properties of the DSN
memory.
The method continues at step 584 where the first and second storage
units establish, between the first and second storage units a
storage migration mechanism for migrating storage of data between
the first and second storage units based on the updated properties
of the DSN memory. The establishing of the storage migration
mechanism may include identifying an address range to migrate,
identifying stored data having an address within the address range
to migrate, establishing a data migration list that includes the
identified stored data, establishing a data migration pattern for
migrating the identified stored data between the first and second
storage units, and updating the data migration list as the
identified stored data is migrated between the first and second
storage units. The establishing of the storage migration mechanism
may further include the first or second storage units determining,
based on non-updated properties of the DSN memory, a source storage
unit of the first and second storage units, determining, based on
the updated properties of the DSN memory, a destination storage
unit of the first and second storage units, and sending the
identified stored data from the source storage unit to the
destination storage unit.
While migrating the storage of data between the first and second
storage units in accordance with the storage migration mechanism,
the method continues at step 586 where the first storage unit or
the second storage unit receives a data access request (e.g., new
data object write request, new revision data object write request,
read request) regarding data effected by the migrating the storage
of data between the first and second storage units. The receiving
the data access request may include receiving the data access
request by the first storage unit when the data access request was
created in accordance with the updated properties of DSN memory and
receiving the data access request by the second storage unit when
the data access request was created in accordance with non-updated
properties of DSN memory.
The method continues at step 588 where the first or second storage
unit determines status of the migrating storage of data between the
first and second storage units. The determining of the status may
be facilitated in accordance with a status determining approach
based on a type of the data access request (e.g., read request, new
write request, revision write request). When the type of the data
access request is the read request, the determining the status of
the migrating storage of the data includes accessing the migration
list of data being migrated between the first and second storage
units, determining whether a data object of the read request has
been migrated based on the migration list, when the data object has
been migrated, indicating the status as migrated to destination,
and when the data object has not been migrated, indicating the
status as not migrated to destination.
When the type of the data access request is the new write request,
the determining the status of the migrating storage of the data
includes, when the first and second storage units possess the
updated properties of the DSN memory, setting the status for the
new write request as write to destination. When the type of the
data access request is the revision write request for a revised
data object, the determining the status of the migrating storage of
the data includes accessing the migration list of data being
migrated between the first and second storage units, determining
whether a predetermined number (e.g., all or almost all) of data
objects on the migration list have been migrated to a destination,
when the predetermined number of data objects have been migrated,
indicating the status as migrated to destination, and when the
predetermined number of data objects have not been migrated,
indicating the status as not migrated to destination.
The method continues at step 590 where the first storage unit or
the second storage unit determines which of the first and second
storage units is to process the data access request based on the
status to produce a determined storage unit. The determining may be
based on the type of the data access request. When the type of the
data access request is the read request, the determining the
determined storage unit includes determining that the first storage
unit is the determined storage unit when the read request was
created based on non-updated properties of the DSN memory and the
status is not migrated to destination, determining that the second
storage unit is the determined storage unit when the read request
was created based on the non-updated properties of the DSN memory
and the status is migrated to destination, determining that the
first storage unit is the determined storage unit when the read
request was created based on updated properties of the DSN memory
and the status is not migrated to destination, and determining that
the second storage unit is the determined storage unit when the
read request was created based on the updated properties of the DSN
memory and the status is migrated to destination.
When the type of the data access request is the new write request,
the determining the determined storage unit includes when the
status indicates write to destination, performing an updated
scoring function using one or more properties of the new write
request and one or more properties of the updated properties of the
DSN memory to identify the second storage unit as the determined
storage unit. When the type of the data access request is the
revision write request for the revised data object, the determining
the determined storage unit includes when the status indicates
migrated to destination, identifying the second storage unit as the
destination and as the determined storage unit, and when the status
indicates not migrated to destination, identifying the first
storage unit as a source and as the determined storage unit.
The method continues at step 592 where the determined storage unit
processes the data access request. The processing may be based on
the type of the data access request. When the type of the data
access request is the read request, the processing the data access
request includes the determined storage unit processes the read
request. The processing may include forwarding, by another storage
unit, the read request to the determined storage unit. When the
type of the data access request is the new write request, the
processing the data access includes storing the data object by the
second storage unit and updating the migration list to include that
the data object has been migrated to the destination. The
processing may include forwarding the new write request to the
determined storage unit. When the type of the data access request
is the revision write request for the revised data object, the
processing the data access includes, when the status indicates
migrated to destination, storing the revised data object by the
second storage unit, and updating the migration list to include
that the revised data object has been migrated to the destination,
and, when the status indicates not migrated to the destination,
storing the revised data object by the first storage unit, and
updating the migration list to include that the revised data object
has not been migrated to the destination.
The method described above in conjunction with the processing
module can alternatively be performed by other modules of the
dispersed storage network or by other devices. In addition, at
least one memory section (e.g., a non-transitory computer readable
storage medium) that stores operational instructions can, when
executed by one or more processing modules of one or more computing
devices of the dispersed storage network (DSN), cause the one or
more computing devices to perform any or all of the method steps
described above.
FIG. 46A is a schematic block diagram of another embodiment of a
distributed storage and task network (DSTN) that includes the
distributed storage and task (DST) processing unit 16 of FIG. 1,
the network 24 of FIG. 1, and the DSTN module 22 of FIG. 1. The DST
processing unit 16 includes the DST client module 34 of FIG. 1 and
a decentralized agreement module 600. The decentralized agreement
module 600 may be implemented utilizing the decentralized agreement
module 350 of FIG. 40A. The DSTN module 22 includes at least one
set of DST execution (EX) units 1-n. Each DST execution unit may be
implemented utilizing the DST execution unit 36 of FIG. 1. Each DST
execution unit includes the distributed task (DT) execution module
90 of FIG. 3.
The DSTN functions to execute a task 94 to generate a result 104.
For example, the DST client module 34 generates partial tasks 98
from a received task 94, selects one or more DST execution units
for execution of the partial tasks 98 using a decentralized
agreement function, sends, via the network 24, the partial tasks 98
to the one or more selected DST execution units, receives partial
results 102, generates a result 104 based on the partial results
102, and outputs the results 104 to a requesting entity. The
selecting utilizing the decentralized agreement function includes
utilizing location weights associated with each DT execution module
90, where the location weight is associated with a partial task
execution capability level. For example, the location weight of 800
is associated with the DT execution module 90 of DST execution unit
1, a location weight of 400 associated with the DT execution module
90 of DST execution unit 2, etc. In a further example of operation,
the DST client module 34 receives the task 94 for execution. The
DST client module 34 obtains the location weights for each DT
execution module 90 of the set of DST execution units 1-n. The
obtaining includes at least one of performing a lookup, receiving,
and issuing a query to at least some of the DST execution units.
Having obtained the location weights, the DST client module 34
obtains ranked scoring information 604 for the plurality of DT
execution modules 90 based on the location weights. For example,
the DST client module 34 issues a ranked scoring information
request 602 to the decentralized agreement module 600, where the
request 602 includes the location weights of each DT execution
module 90, a DT execution module identifier, a DT execution module
group identifier, and a task identifier of the task 94; and
receives the ranked scoring information.
Having obtained the ranked scoring information 604, the DST client
module 34 determines a number of DT execution modules 90 for
assignment to the task 94. The determining may be based on one or
more of a capability level of the DT execution modules 90 and
scores associated with each DT execution module of the ranked
scoring information 604. For example, the DST client module 34
selects five DT execution modules 90 associated with a highest five
scores of the ranked scoring information 604, where the five DT
execution modules 90 are associated with sufficient task execution
capability levels to execute five partial tasks 98 in accordance
with a required time frame.
Having determined the number of DT execution modules 90, the DST
client module 34 generates the number of partial tasks 98 based on
the task 94. For example, the DST client module 34 generates one
partial task 98 for each DT execution module 90 of the selected
five DT execution modules 90. As another example, the DST client
module 34 generates two partial tasks for a DT execution module 90
associated with a highest score and generates one partial task for
each remaining DT execution module 90 of the selected five DT
execution modules 90.
The DST client module 34 issues the generated partial tasks 98, via
the network 24, to the selected DT execution modules 90. The DST
client module 34 receives partial results 102 and issues the result
104 based on the received partial results 102.
FIG. 46B is a flowchart illustrating an example of selecting task
execution resources. The method begins or continues at step 606
where a processing module (e.g., of a distributed storage and task
(DST) client module) receives a task for execution, where the task
is associated with a task identifier (ID). The method continues at
step 608 where the processing module obtains location weights for
each of the plurality of task execution units. The obtaining
includes at least one of receiving the location weights with the
task, performing a lookup, initiating a query, and receiving a
query response.
The method continues at step 610 where the processing module
determines ranked scoring information for the plurality of task
execution units based on the location weights. For example, the
processing module performs a decentralized agreement protocol
function using the location weights of each task execution unit, a
task execution unit identifier, a task execution unit group
identifier, and the task ID to produce the ranked scoring
information.
The method continues at step 612 where the processing module
determines a number of resources to assign to execution of the task
based on the task. The determining may be based on one or more of a
desired task execution completion time frame, resource
availability, and a number of task execution units associated with
a score above a score threshold level. The method continues at step
614 where the processing module generates at least one partial task
for each of the number of resources executing the task. For
example, the processing module divides up the task into partial
tasks. As another example, the processing module replicates partial
tasks. As yet another example, the processing module replicates the
task as the partial tasks.
The method continues at step 616 where the processing module
selects the number of resources of the plurality of task execution
units based on the ranked scoring information to produce one or
more selected task execution units. For example, the processing
module selects task execution units associated with highest scores
of the ranked scoring information in accordance with the determined
number of resources executing the task.
The method continues at step 618 where the processing module sends
a corresponding partial task to each of the one or more selected
task execution units. The method continues at step 620 where the
processing module issues a result based on received partial
results.
FIG. 47A is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) that includes the distributed
storage and task (DST) processing unit 16 of FIG. 1, the network 24
of FIG. 1, and a DST execution (EX) unit pool 622. The DST
processing unit 16 includes the DST client module 34 of FIG. 1. The
DST execution unit pool 622 includes at least one set of DST
execution units 1-n. Each DST execution unit may be implemented
utilizing the DST execution unit 36 of FIG. 1.
The DSN functions to update storage unit configuration of the DST
execution unit pool 622, where the DST execution unit pool 622
stores pluralities of sets of encoded data slices. The updating of
the storage unit configuration includes one or more of activating a
storage unit, deactivating a storage unit, upgrading storage unit
software, upgrading storage unit hardware, and performing a
maintenance test.
In an example of operation, each DST execution unit determines a
slice storage status for a DSN address range based on monitoring
rebuilding messages. The slice storage status includes one or more
of the DSN address range, a number of storage errors, a status
rating, an overall slice storage status, and a number of favorably
stored encoded data slices. For example, DST execution unit 1
monitors rebuilding messages 1 and identifies generates storage
status 1 based on the monitored rebuilding messages 1. The
rebuilding messages include at least one of a list slice requests,
a list digest request, and a store rebuilt slice request. As
another example, the DST execution unit 1 indicates a favorable
slice storage status when rebuilding activity for the DSN address
range over a time frame is less than a rebuilding threshold
level.
With each DST execution unit having determined associated slice
storage status, the DST client module 34 receives, via the network
24, slice storage status 1-n. Having received the slice storage
status, the DST client module 34 determines to update the storage
unit configuration of one or more storage units of the set of
storage units. The determining may be based on one or more of
interpreting an error message, receiving a request, detecting
suffer availability, detecting new hardware availability, detecting
a software error, initiating a query, and receiving a query
response.
Having determined to update the storage unit configuration, the DST
client module 34 determines whether to update the storage unit
configuration based on the received slices storage status. For
example, the DST client module 34 indicates to update the storage
unit configuration when at least a threshold number of storage
units associated with favorable slice storage status for the DSN
address range. When updating the storage unit configuration, the
DST client module 34 issues storage unit configuration updates 624
to one or more of the DST execution units.
FIG. 47B is a flowchart illustrating an example of updating storage
unit configuration information. The method begins or continues at
step 626 where a processing module of one or more processing
modules of a dispersed storage network (e.g., of a distributed
storage and task (DST) client module, of a storage unit)
determines, for each storage unit of a set of storage units, a
slice storage status of a dispersed storage network (DSN) address
range. The determining includes one or more of receiving the
status, initiating a query, and receiving a query response that
includes the status. The determining may include determining, by
each storage unit, the storage status. For example, a storage unit
indicates favorable slice storage status when a number of
rebuilding messages is less than a rebuilding message threshold
level.
The method continues at step 628 where the processing module
obtains the slice storage status of each storage unit of the set of
storage units. The obtaining includes at least one of receiving,
initiating a query, and receiving a query response. The method
continues at step 630 where the processing module determines to
update storage unit configuration of one or more storage units of
the set of storage units. The determining includes one or more of
interpreting a maintenance schedule, receiving a new software
version for uploading to one or more the storage units, detecting
new hardware installed and a storage unit, and determining to
perform a test.
The method continues at step 632 where the processing module
determines whether to update the storage unit configuration based
on the storage unit configuration of at least some storage units of
the set of storage units. For example, the processing module
indicates to update the storage unit configuration when a threshold
number of storage units associated with favorable slice storage
status for the DSN address range.
When updating the storage unit configuration, the method continues
at step 634 where the processing module issues a storage unit
configuration update to one or more of the storage units of the set
of storage units. The issuing includes one or more of initiating a
test, indicating utilizing new suffer version, issuing
configuration information for new hardware, initiating a
maintenance cycle, etc.
FIG. 48A is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) that includes the distributed
storage and task (DST) processing unit 16 of FIG. 1, the network 24
of FIG. 1, and at least two DST execution (EX) unit pools 1-2. Each
DST execution unit pool includes a set of DST execution units 1-n.
Each DST execution unit may be implemented utilizing the DST
execution unit 36 of FIG. 1. The DST processing unit 16 includes a
decentralized agreement module 636 and a DST client module 34. The
decentralized agreement module 636 may be implemented utilizing the
decentralized agreement module 350 of FIG. 40A.
The DSN functions to migrate encoded data slices stored in the DST
execution unit pool 1 to the DST execution unit pool 2 and to
process writing additional data as further encoded data slices to
at least one of the DST execution unit pool 1 and DST execution
unit pool 2 subsequent to initiation of the migration and prior to
conclusion of the migration. For example, DST execution unit pool 2
is newly commissioned as a replacement to DST execution unit pool 1
which is at an end-of-life.
In an example of operation, the DST client module 34 determines to
replace the DST execution unit pool 1, where one or more first DSN
address ranges are associated with the DST execution unit pool 1.
Hereafter, the DST execution unit pool 1 may be interchangeably
referred to as a first storage pool and the DST execution unit pool
2 may be interchangeably referred to as a second storage pool. The
determining may be based on one or more of interpreting a
replacement schedule, receiving a request, and detecting an
error.
Having determined to replace the first storage pool, the DST client
module 34 identifies a second storage pool to replace the first
storage pool. Alternatively, the DST client module 34 identifies a
second and third storage pool to replace the first storage pool.
The identifying includes one or more of detecting a new storage
pool, receiving a manager input, identifying a storage pool
associated with sufficient available capacity, and utilizing a
decentralized agreement function to identify a most favorable
storage pool as the second storage pool. For example, the DST
client module 34 issues a ranked scoring information request 638 to
the decentralized agreement module 636, where the request 638
includes one or more of a DSN address of the first DSN address
ranges, location weights of alternative storage pools, and
identifiers of the alternative storage pools, and receives ranked
scoring information 640.
Having identified the second storage pool, the DST client module 34
issues migration messages 648 to the first and second storage pools
to initiate migration of encoded data slices from the first storage
pool to the second storage pool. The migration messages indicate
slice names associated with at least one of all encoded data slices
and encoded data slices associated with slice names within a DSN
address range. For example, the first storage pool issues, via the
network 24, transfer slice requests 646 to the second storage pool,
where the transfer slice requests 646 include at least some of the
encoded data slices for migration.
When receiving a write slice request 642 issued by the DST client
module 34, by the first storage pool, prior to conclusion of the
migration of the encoded data slices, one or more of the DST
execution units of the first storage pool forwards a write slice
request as a redirected write slice request 644 to the
corresponding DST execution units of the second storage pool for
storage. For example, the DST client module 34 receives data for
storage, encodes the data using a dispersed storage error coding
function to produce at least one set of encoded data slices, and
issues a set of write slice requests 642 to the first storage pool,
where the write slice requests 642 includes the at least one set of
encoded data slices.
When the migration of the encoded data slices has concluded, the
DST client module 34 disassociates the one or more first DSN
address ranges from the first storage pool and associates the one
or more first DSN address ranges with the second storage pool.
Alternatively, or in addition to, the DST client module 34 updates
location weights associated with DST execution units of the DST
execution unit pool 2, updates a DSN directory, and updates a
dispersed hierarchical index.
FIG. 48B is a flowchart illustrating another example of migrating
slices. The method begins or continues at step 650 where a
processing module (e.g., of a distributed storage and task (DST)
client module) determines to replace a first storage pool of a
dispersed storage network (DSN). The determining may include one or
more of receiving a request, detecting one or more storage errors,
and interpreting a replacement schedule. The method continues at
step 652 where the processing module identifies a second storage
pool to replace the first storage pool. The identifying includes at
least one of detecting a storage pool, receiving a manager input,
and identifying a storage pool associated with available capacity
greater than or equal to capacity of the first storage pool.
The method continues at step 654 where the processing module issues
migration messages to at least one of the first storage pool and
the second storage pool to initiate migration of encoded data
slices from the first storage pool to the second storage pool. The
issuing includes at least one of instructing the first storage pool
to issue transfer requests to the second storage pool, instructing
the second storage pool to request slices from the first storage
pool, and notifying at least one of the first and second storage
pools of an open migration status.
When receiving a write request by the first storage pool, prior to
conclusion of the migration, the method continues at step 656 where
the first storage pool forwards the write slice request to the
second storage pool. For example, a storage unit of the second
storage pool receives the write slice request, determines status of
the migration, interprets the status to indicate that the migration
status is open, and sends the write slice request to a
corresponding storage unit of the second storage pool.
Upon conclusion of the migration, the method continues at step 658
where the processing module disassociates slice names previously
associated with the first storage pool from the first storage pool
and associates the slice names with the second storage pool.
Alternatively, or in addition to, the processing module zeros out a
location weight associated with a decentralized agreement function
for the first storage pool, increases a location weight associated
with the second storage pool, updates a DSN directory, and updates
a DSN address to physical location table.
FIG. 49A is a schematic block diagram of another embodiment of a
dispersed storage network (DSN) that includes a set of distributed
storage and task (DST) execution (EX) units 1-n and the network 24
of FIG. 1. Each DST execution unit includes the processing module
84 of FIG. 3 and a plurality of memories. Hereafter, a DST
execution unit may be interchangeably referred to as a storage
unit. Each memory may be associated with one or more properties.
The properties may include one or more of a manufacturer, a model
number, a serial number range, the manufacturing date, hours of
operation, expected service life, expected remaining service life,
hardware version, software version, firmware version, and a failure
rate.
Each DST execution unit includes one or more subgroups of memories
of the plurality of memories, where each subgroup is associated
with a property class. Each property class includes one or more
similar properties. For example, DST execution unit 1 includes
memories A-1 through A-m that are associated with a property class
A, memories C-1 through C-m that are associated with a property
class C, etc.
The DSN functions to store data as a plurality of sets of encoded
data slices and to rebalance storage of the encoded data slices
within each DST execution unit based on the property classes. In an
example of operation, the processing module 84 of any storage unit
identifies one or more property classes of a plurality of memory
devices associated with the storage unit. The identifying includes
at least one of initiating a test, interpreting a test result,
accessing a list, receiving, and interpreting DSN registry
information.
Having identified the one or more property classes, the processing
module 84 obtains a priority of usage level for each property
class. The obtaining includes at least one of determining,
receiving, initiating a query, and receiving a query response. For
example, the processing module 84 determines a priority of usage
level for the property class A as a highest level when memory
devices associated with the property class A are associated with a
favorable (e.g., lower than average) historical failure rate.
Having obtained the priority of usage level, the processing module
84 identifies associations of encoded data slices of common data
objects with one or more property classes. For example, the
processing module 84 accesses a slice name to memory device
identifier table. Having identified the associations, the
processing module 84 obtains configuration information 660 for the
set of storage units that includes the storage unit. The
configuration information 660 includes one or more of a list of
property classes, DSN addresses associated with each property
class, a number of memory devices for each property class, known
issues with a property class, and a priority of usage level for
each property class. For example, the processing module issues, via
the network 24, configuration information requests to other storage
units and receives configuration information 660 from the other
storage units.
Having obtained the configuration information 660, the processing
module 84 determines an updated configuration for the plurality of
memory devices of the storage unit based on one or more of the
property of usage levels, the associations, and the configuration
information 660. For example, the processing module 84 determines
the updated configuration to result in utilizing a maximum number
of memories associated with different manufacturers for encoded
data slices associated with a common data object to improve
diversity based reliability. As another example, the processing
module 84 determines the updated configuration to move encoded data
slices of the common data object from memories that are two years
old to memories that are one year old to improve retrieval
reliability. As yet another example, the processing module 84
determines the updated configuration to move the encoded data
slices of the common data object away from memories associated with
a known faulty firmware version to other memories. Having
determined the updated configuration, the processing module 84
facilitates migration of one or more encoded data slices in
accordance with the updated configuration.
FIG. 49B is a flowchart illustrating another example of migrating
slices. The method begins or continues at step 662 where a
processing module (e.g., of a distributed storage and task (DST)
execution unit) identifies one or more property classes of a
plurality of memory devices associated with a storage unit of a set
of storage units. The identifying includes at least one of
initiating a test, interpreting a test result, accessing a list,
interpreting dispersed storage network (DSN) registry information,
and receiving.
For each property class, the method continues at step 664 where the
processing module obtains a priority of usage level associated with
the property class. The obtaining includes at least one of
determining, receiving, initiating a query, and receiving a query
response. The method continues at step 666 where the processing
module identifies associations of encoded data slices of common
data objects with one or more property classes. The identifying
includes at least one of accessing a DSN address to physical
location table, accessing a slice list, and utilizing a
decentralized agreement function.
The method continues at step 668 where the processing module
obtains configuration information for the set of storage units. The
obtaining includes at least one of initiating a configuration
information request, receiving a configuration information
response, and accessing the DSN registry information.
The method continues at step 670 where the processing module
determines an updated configuration for the association of the
encoded data slices with the one or more property classes. The
determining may be based on one or more of the property of usage
levels, the associations, and the configuration information. For
example, the processing module aligns storage of slices in a common
property class with other units of the set of storage units. As
another example, the processing module facilitates moving slices
from a property class with a known issue to another property class
without an issue. As yet another example, the processing module
moves slices from a memory of a property class with a least
favorable usage level to another memory associated with a property
class with a more favorable usage level.
The method continues at step 672 where the processing module
facilitates migration of one or more encoded data slices in
accordance with the updated configuration. The facilitating
includes one or more of issuing a migration request, retrieving
slices, stored slices, updating a slice name to physical location
table, and updating location weights associated with memory devices
of the storage unit in accordance with the decentralized agreement
function.
As may be used herein, the terms "substantially" and
"approximately" provides an industry-accepted tolerance for its
corresponding term and/or relativity between items. Such an
industry-accepted tolerance ranges from less than one percent to
fifty percent and corresponds to, but is not limited to, component
values, integrated circuit process variations, temperature
variations, rise and fall times, and/or thermal noise. Such
relativity between items ranges from a difference of a few percent
to magnitude differences. As may also be used herein, the term(s)
"operably coupled to", "coupled to", and/or "coupling" includes
direct coupling between items and/or indirect coupling between
items via an intervening item (e.g., an item includes, but is not
limited to, a component, an element, a circuit, and/or a module)
where, for indirect coupling, the intervening item does not modify
the information of a signal but may adjust its current level,
voltage level, and/or power level. As may further be used herein,
inferred coupling (i.e., where one element is coupled to another
element by inference) includes direct and indirect coupling between
two items in the same manner as "coupled to". As may even further
be used herein, the term "operable to" or "operably coupled to"
indicates that an item includes one or more of power connections,
input(s), output(s), etc., to perform, when activated, one or more
its corresponding functions and may further include inferred
coupling to one or more other items. As may still further be used
herein, the term "associated with", includes direct and/or indirect
coupling of separate items and/or one item being embedded within
another item. As may be used herein, the term "compares favorably",
indicates that a comparison between two or more items, signals,
etc., provides a desired relationship. For example, when the
desired relationship is that signal 1 has a greater magnitude than
signal 2, a favorable comparison may be achieved when the magnitude
of signal 1 is greater than that of signal 2 or when the magnitude
of signal 2 is less than that of signal 1.
As may also be used herein, the terms "processing module",
"processing circuit", and/or "processing unit" may be a single
processing device or a plurality of processing devices. Such a
processing device may be a microprocessor, micro-controller,
digital signal processor, microcomputer, central processing unit,
field programmable gate array, programmable logic device, state
machine, logic circuitry, analog circuitry, digital circuitry,
and/or any device that manipulates signals (analog and/or digital)
based on hard coding of the circuitry and/or operational
instructions. The processing module, module, processing circuit,
and/or processing unit may be, or further include, memory and/or an
integrated memory element, which may be a single memory device, a
plurality of memory devices, and/or embedded circuitry of another
processing module, module, processing circuit, and/or processing
unit. Such a memory device may be a read-only memory, random access
memory, volatile memory, non-volatile memory, static memory,
dynamic memory, flash memory, cache memory, and/or any device that
stores digital information. Note that if the processing module,
module, processing circuit, and/or processing unit includes more
than one processing device, the processing devices may be centrally
located (e.g., directly coupled together via a wired and/or
wireless bus structure) or may be distributedly located (e.g.,
cloud computing via indirect coupling via a local area network
and/or a wide area network). Further note that if the processing
module, module, processing circuit, and/or processing unit
implements one or more of its functions via a state machine, analog
circuitry, digital circuitry, and/or logic circuitry, the memory
and/or memory element storing the corresponding operational
instructions may be embedded within, or external to, the circuitry
comprising the state machine, analog circuitry, digital circuitry,
and/or logic circuitry. Still further note that, the memory element
may store, and the processing module, module, processing circuit,
and/or processing unit executes, hard coded and/or operational
instructions corresponding to at least some of the steps and/or
functions illustrated in one or more of the Figures. Such a memory
device or memory element can be included in an article of
manufacture.
The present invention has been described above with the aid of
method steps illustrating the performance of specified functions
and relationships thereof. The boundaries and sequence of these
functional building blocks and method steps have been arbitrarily
defined herein for convenience of description. Alternate boundaries
and sequences can be defined so long as the specified functions and
relationships are appropriately performed. Any such alternate
boundaries or sequences are thus within the scope and spirit of the
claimed invention. Further, the boundaries of these functional
building blocks have been arbitrarily defined for convenience of
description. Alternate boundaries could be defined as long as the
certain significant functions are appropriately performed.
Similarly, flow diagram blocks may also have been arbitrarily
defined herein to illustrate certain significant functionality. To
the extent used, the flow diagram block boundaries and sequence
could have been defined otherwise and still perform the certain
significant functionality. Such alternate definitions of both
functional building blocks and flow diagram blocks and sequences
are thus within the scope and spirit of the claimed invention. One
of average skill in the art will also recognize that the functional
building blocks, and other illustrative blocks, modules and
components herein, can be implemented as illustrated or by discrete
components, application specific integrated circuits, processors
executing appropriate software and the like or any combination
thereof.
The present invention may have also been described, at least in
part, in terms of one or more embodiments. An embodiment of the
present invention is used herein to illustrate the present
invention, an aspect thereof, a feature thereof, a concept thereof,
and/or an example thereof. A physical embodiment of an apparatus,
an article of manufacture, a machine, and/or of a process that
embodies the present invention may include one or more of the
aspects, features, concepts, examples, etc., described with
reference to one or more of the embodiments discussed herein.
Further, from figure to figure, the embodiments may incorporate the
same or similarly named functions, steps, modules, etc., that may
use the same or different reference numbers and, as such, the
functions, steps, modules, etc., may be the same or similar
functions, steps, modules, etc., or different ones.
While the transistors in the above described figure(s) is/are shown
as field effect transistors (FETs), as one of ordinary skill in the
art will appreciate, the transistors may be implemented using any
type of transistor structure including, but not limited to,
bipolar, metal oxide semiconductor field effect transistors
(MOSFET), N-well transistors, P-well transistors, enhancement mode,
depletion mode, and zero voltage threshold (VT) transistors.
Unless specifically stated to the contra, signals to, from, and/or
between elements in a figure of any of the figures presented herein
may be analog or digital, continuous time or discrete time, and
single-ended or differential. For instance, if a signal path is
shown as a single-ended path, it also represents a differential
signal path. Similarly, if a signal path is shown as a differential
path, it also represents a single-ended signal path. While one or
more particular architectures are described herein, other
architectures can likewise be implemented that use one or more data
buses not expressly shown, direct connectivity between elements,
and/or indirect coupling between other elements as recognized by
one of average skill in the art.
The term "module" is used in the description of the various
embodiments of the present invention. A module includes a
processing module, a functional block, hardware, and/or software
stored on memory for performing one or more functions as may be
described herein. Note that, if the module is implemented via
hardware, the hardware may operate independently and/or in
conjunction software and/or firmware. As used herein, a module may
contain one or more sub-modules, each of which may be one or more
modules.
While particular combinations of various functions and features of
the present invention have been expressly described herein, other
combinations of these features and functions are likewise possible.
The present invention is not limited by the particular examples
disclosed herein and expressly incorporates these other
combinations.
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